Aim/Purpose: The dynamic nature of the information systems (IS) field presents educators with the perpetual challenge of keeping course offerings current and relevant. This paper describes the process at a College of Business (COB) to redesign the introductory IS course to better prepare students for advanced business classes and equip them with interdisciplinary knowledge and skills demanded in today’s workplace. Background: The course was previously in the Computer Science (CSC) Department, itself within the COB. However, an administrative restructuring resulted in the CSC department’s removal from the COB and left the core course in limbo. Methodology: This paper presents a case study using focus groups with students, faculty, and advisory council members to assess the value of the traditional introductory course. A survey was distributed to students after implementation of the newly developed course to assess the reception of the course. Contribution: This paper provides an outline of the decision-making process leading to the course redesign of the introductory IS course, including the context and the process of a new course development. Practical suggestions for implementing and teaching an introductory IS course in a business school are given. Findings: Focus group assessment revealed that stakeholders rated the existing introductory IS course of minimal value as students progressed through the COB program, and even less upon entering the workforce. The findings indicated a complete overhaul of the course was required. Recommendations for Practitioners: The subject of technology sometimes requires more than a simple update to the curriculum. When signs point to the need for a complete overhaul, this paper gives practical guidance supplemented with relevant literature for other academicians to follow. Recommendation for Researchers: Students are faced with increasing pressure to be proficient with the latest technology, in both the classroom where educators are trying to prepare them for the modern workplace, as well as the organization which faces an even greater pressure to leverage the latest technology. The newly designed introductory IS course provides students, and eventually organizations, a better measure of this proficiency. Future Research: Future research on the efficacy of this new course design should include longitudinal data to determine the impact on graduates, and eventually the assessment of those graduates’ performance in the workplace.

Aim/Purpose: The aim of this article is to develop a tool to detect plagiarism in real time amongst students being evaluated for learning in a computer-based assessment setting. Background: Cheating or copying all or part of source code of a program is a serious concern to academic institutions. Many academic institutions apply a combination of policy driven and plagiarism detection approaches. These mechanisms are either proactive or reactive and focus on identifying, catching, and punishing those found to have cheated or plagiarized. To be more effective against plagiarism, mechanisms that detect cheating or colluding in real-time are desirable. Methodology: In the development of a tool for real-time plagiarism prevention, literature review and prototyping was used. The prototype was implemented in Delphi programming language using Indy components. Contribution: A real-time plagiarism detection tool suitable for use in a computer-based assessment setting is developed. This tool can be used to complement other existing mechanisms. Findings: The developed tool was tested in an environment with 55 personal computers and found to be effective in detecting unauthorized access to internet, intranet, and USB ports on the personal computers. Recommendations for Practitioners: The developed tool is suitable for use in any environment where computer-based evaluation may be conducted. Recommendation for Researchers: This work provides a set of criteria for developing a real-time plagiarism prevention tool for use in a computer-based assessment. Impact on Society: The developed tool prevents academic dishonesty during an assessment process, consequently, inculcating confidence in the assessment processes and respectability of the education system in the society. Future Research: As future work, we propose a comparison between our tool and other such tools for its performance and its features. In addition, we want to extend our work to include testing for scalability of the tool to larger settings.

Aim/Purpose: This paper presents a data mining approach for analyzing responses to advanced declarative programming questions. The goal of this research is to find a model that can explain the results obtained by students when they perform exams with Constructed Response questions and with equivalent Multiple-Choice Questions. Background: The assessment of acquired knowledge is a fundamental role in the teaching-learning process. It helps to identify the factors that can contribute to the teacher in the developing of pedagogical methods and evaluation tools and it also contributes to the self-regulation process of learning. However, better format of questions to assess declarative programming knowledge is still a subject of ongoing debate. While some research advocates the use of constructed responses, others emphasize the potential of multiple-choice questions. Methodology: A sensitivity analysis was applied to extract useful knowledge from the relevance of the characteristics (i.e., the input variables) used for the data mining process to compute the score. Contribution: Such knowledge helps the teachers to decide which format they must consider with respect to the objectives and expected students results. Findings: The results shown a set of factors that influence the discrepancy between answers in both formats. Recommendations for Practitioners: Teachers can make an informed decision about whether to choose multiple-choice questions or constructed-response taking into account the results of this study. Recommendation for Researchers: In this study a block of exams with CR questions is verified to complement the area of learning, returning greater performance in the evaluation of students and improving the teaching-learning process. Impact on Society: The results of this research confirm the findings of several other researchers that the use of ICT and the application of MCQ is an added value in the evaluation process. In most cases the student is more likely to succeed with MCQ, however if the teacher prefers to evaluate with CR other research approaches are needed. Future Research: Future research must include other question formats.

Aim/Purpose: This paper aims to explore whether having state Computer Science standards in place will increase young children’s exposure to coding and powerful ideas from computer science in the early years. Background: Computer science education in the K-2 educational segment is receiving a growing amount of attention as national and state educational frameworks are emerging. By focusing on the app ScratchJr, the most popular free introductory block-based programming language for early childhood, this paper explores if there is a relationship between the presence of state frameworks and ScratchJr’s frequency of use. Methodology: This paper analyzes quantitative non-identifying data from Google Analytics on users of the ScratchJr programming app. Google Analytics is a free tool that allows access to user activity as it happens in real time on the app, as well as audience demographics and behavior. An analysis of trends by state, time of year, type of in-app activities completed, and more are analyzed with a specific focus on comparing states with K-12 Computer Science in place versus those without. Contribution: Results demonstrate the importance of having state standards in place to increase young children’s exposure to coding and powerful ideas from computer science in the early years. Moreover, we see preliminary evidence that states with Computer Science standards in place support skills like perseverance and debugging through ScratchJr. Findings: Findings show that in the case of ScratchJr, app usage decreases during the summer months and on weekends, which may indicate that coding with ScratchJr is more often happening in school than at home. Results also show that states with Computer Science standards have more ScratchJr users on average and have more total sessions with the app on average. Results also show preliminary evidence that states with Computer Science standards in place have longer average session duration as well as a higher average number of users returning to edit an existing project. Recommendations for Practitioners: Successful early childhood computer science education programs must teach powerful ideas from the discipline of computer science in a developmentally appropriate way, provide means for self-expression, prompt debugging and problem solving, and offer a low-floor/high-ceiling interface for both novices and experts. Practitioners should be aware in drops in computer science learning during the summer months when school is not in session. Recommendation for Researchers: Researchers should consider the impact of state and national frameworks on computer science learning and skills mastered during the early childhood years. Researchers should look for ways to continue engaging students in computer science education during times when school is not in session. Impact on Society: Results demonstrate the importance of having state CS standards in place to increase young children’s exposure to coding and powerful ideas from computer science in the early years. Moreover, we see preliminary evidence that states with Computer Science standards in place support skills like perseverance and debugging through ScratchJr. Future Research: Future research should continue collecting Google Analytics from the ScratchJr app and track changes in usage. Future research should also collect analytics from a wide range of programming applications for young children to see if the trends identified here are consistent across different apps.

Aim/Purpose: The main aim of this study was modeling a collaborative process for knowledge visualization, via the creation of infographics. Background: As an effective method for visualizing complex information, creating infographics requires learners to generate and cultivate a deep knowledge of content and enables them to concisely visualize and share this knowledge. This study investigates creating infographics as a knowledge visualization process for collaborative learning situations by integrating the infographic design model into the team-based and technology-mediated Bridge21 learning model. Methodology: This study was carried out using an educational design perspective by conducting three main cycles comprised of three micro cycles: analysis and exploration; design and construction; evaluation and reflection. The process and the scaffolding were developed and enhanced from cycle to cycle based on both qualitative and quantitative methods by using the infographic design rubric and researcher observations acquired during implementation. Respectively, twenty-three, twenty-four, and twenty-four secondary school students participated in the infographic creation process cycles. Contribution: This research proposes an extensive step-by-step process model for creating infographics as a method of visualization for learning. It is particularly relevant for working with complex information, in that it enables collaborative knowledge construction and sharing of condensed knowledge. Findings: Creating infographics can be an effective method for collaborative learning situations by enabling knowledge construction, visualization and sharing. The Bridge21 activity model constituted the spine of the infographic creation process. The content generation, draft generation, and visual and digital design generation components of the infographic design model matched with the investigate, plan and create phases of the Bridge21 activity model respectively. Improvements on infographic design results from cycle to cycle suggest that the revisions on the process model succeeded in their aims. The rise in each category was found to be significant, but the advance in visual design generation was particularly large. Recommendations for Practitioners: The effectiveness of the creation process and the quality of the results can be boosted by using relevant activities based on learner prior knowledge and skills. While infographic creation can lead to a focus on visual elements, the importance of wording must be emphasized. Being a multidimensional process, groups need guidance to ensure effective collaboration. Recommendation for Researchers: The proposed collaborative infographic creation process could be structured and evaluated for online learning environments, which will improve interaction and achievement by enhancing collaborative knowledge creation. Impact on Society: In order to be knowledge constructors, innovative designers, creative communicators and global collaborators, learners need to be surrounded by adequate learning environments. The infographic creation process offers them a multidimensional learning situation. They must understand the problem, find an effective way to collect information, investigate their data, develop creative and innovative perspectives for visual design and be comfortable for using digital creation tools. Future Research: The infographic creation process could be investigated in terms of required learner prior knowledge and skills, and could be enhanced by developing pre-practices and scaffolding.

Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However, most of the studies employed omnibus approaches, i.e. without consideration of different programing concepts and ability levels of the trainee programmers. Such concepts and ability specific errors identification and classifications are needed to advance appropriate intervention strategy. Methodology: A sequential exploratory mixed method design was adopted. The sample was an intact class of 124 Computer Science and Engineering undergraduate students grouped into three achievement levels based on first semester performance in a Java programming course. The submitted codes in the course of second semester exercises were analyzed for possible errors, categorized and grouped across achievement level. The resulting data were analyzed using descriptive statistics as well as Pearson product correlation coefficient. Qualitative analyses through interviews and focused group discussion (FGD) were also employed to identify reasons for the committed errors. Contribution:The study provides a useful concept-based and achievement level specific error log for the teaching of Java programming for beginners. Findings: The results identified 598 errors with Missing symbols (33%) and Invalid symbols (12%) constituting the highest and least committed errors respec-tively. Method and Classes concept houses the highest number of errors (36%) followed by Other Object Concepts (34%), Decision Making (29%), and Looping (10%). Similar error types were found across ability levels. A significant relationship was found between missing symbols and each of Invalid symbols and Inappropriate Naming. Errors made in Methods and Classes were also found to significantly predict that of Other Object concepts. Recommendations for Practitioners: To promote better classroom practice in the teaching of Java programming, findings for the study suggests instructions to students should be based on achievement level. In addition to this, learning Java programming should be done with an unintelligent editor. Recommendations for Researchers: Research could examine logic or semantic errors among novice programmers as the errors analyzed in this study focus mainly on syntactic ones. Impact on Society: The digital age is code-driven, thus error analysis in programming instruction will enhance programming ability, which will ultimately transform novice programmers into experts, particularly in developing countries where most of the software in use is imported. Future Research: Researchers could look beyond novice or beginner programmers as codes written by intermediate or even advanced programmers are still not often completely error free.

Aim/Purpose: In this study, the researchers investigated whether the out-of-class learning approach could help the students to attain any valuable learning outcomes for cybersecurity learning and could enhance the perceived value of cybersecurity education among the students. Background: Cybersecurity learning poses challenges for its students to learn a complicated subject matter and the students may be intimidated by the challenging courses in cybersecurity programs. Therefore, it is essential for the faculty members to devise some mechanisms to promote cybersecurity learning to increase its student retention. The mechanism suggested by this study was the out-of-class learning approach. Methodology: The researchers in this study employed a content analysis and adopted a semiotic method to analyze qualitative data. The researchers also conducted crosstabulation analyses using chi-square tests to detect the significant differences in the emerging learning outcomes from the two different out-of-class learning activities investigated in this study. Contribution: This study addressed the difficulty of cybersecurity education and proposed a viable mechanism to promote the student learning in such a complicated subject matter. Findings: For cybersecurity education, the out-of-class learning approach is a viable pedagogical mechanism that could lead the students to several learning outcomes, including connecting them to the real-life scenarios related to the cybersecurity profession, guiding them to their career choices and development, stimulating their intellectual growth, creating their justification of learning, and raising their cybersecurity awareness. Recommendations for Practitioners: The instructors of any cybersecurity programs should incorporate some out-of-class learning activities into the courses in their programs, especially the introductory-level courses. Additionally, it is important to coordinate the out-of-class learning activities with the in-class lessons to enable the students to justify what they have learned in their classrooms and motivate them to learn more. Recommendation for Researchers: Researchers could look beyond in-class learning and laboratory learning to investigate the impacts of out-of-class learning activities on cybersecurity education to help the students to attain better learning outcomes. Impact on Society: By promoting cybersecurity education, universities and colleges could attain a higher retention rate of the students in their cybersecurity programs. The higher retention rate of the students in cybersecurity programs would help to ease the critical shortage of cybersecurity talent. Future Research: Future research could explore the impacts of other out-of-class learning activities on cybersecurity learning; for example: job shadowing, attending cybersecurity conferences, internship, developing cybersecurity systems or tools for actual customers, working on cybersecurity research with faculty members. Additionally, future studies could investigate the effects of the out-of-class learning approach on promoting other academic programs that are characterized by intensely complex and technical nature, similar to cybersecurity programs.

Aim/Purpose: This paper reports on a case study project which had three goals; to develop a suite of original interactive digital skills e-tutorials to be embedded in undergraduate and postgraduate courses; to evaluate the students’ experience and engagement with the e-tutorials over one semester; and to explore their general attitudes towards online and blended learning. Background: Online and blended learning modes continue to grow in popularity in higher education, with the aim of streamlining and enhancing student learning, supporting collaboration and creativity, and equipping students with the skills they will require to work and live in an increasingly digitized world. This practice-based case study highlights factors which positively and negatively affect user engagement with digital learning objects and explores students’ perceptions of the role of online learning within their academic programs. Methodology: A suite of nine interactive e-tutorials, addressing essential digital literacy skills for university students, was developed through instructor and student peer collaboration using Articulate software, informed by best practice. The e-tutorials were embedded in the institutional Learning Management System for three undergraduate and postgraduate courses, in which digital literacy formed the core learning content, to complement classroom-based learning. Students in these courses were surveyed via SurveyMonkey about their specific experience of using the e-tutorials, as well as their general perceptions of digital literacy and online learning. Eighty-six students in total completed the questionnaire, which consisted of twenty-three closed- and open-ended questions. Contribution: Through highlighting both the positive and the challenging aspects of the students’ reported experience of online learning, this case study contributes useful insights to the body of literature on user engagement with digital learning objects in higher education, as well as students’ perceptions and experience of blended learning. Findings: The e-tutorials were perceived as valuable in reinforcing classroom learning, allowing respondents to revise concepts and materials covered in face-to-face classes, at their own pace and in their own time. Survey responses showed that the accessibility, ease-of-use, design and duration of the e-tutorials were deemed effective in terms of user engagement; however, several technological challenges were identified, such as browser incompatibility, uneven sound quality and general Internet connection issues, which disrupted their learning. Overall, students expressed enjoyment of the learning facilitated by the e-tutorials; however, rather than favoring online learning alone, they expressed a preference for a blended learning environment, with a combination of complementary learning approaches; survey respondents did not generally wish to forego face-to-face classes entirely. Recommendations for Practitioners: Instructors should seek to strategically embed interactive digital learning objects in their courses at defined points of need in a logical structure, e.g., to reinforce classroom-based learning, or to support specific skill development. Potential disruption to learning should be minimized by following best practice guidelines to ensure ease of access, a seamless user experience, and timely feedback, as well as providing adequate support for rapid resolution of technical glitches. Recommendation for Researchers: E-tutorials offer a useful means of exploring ways in which students acquire learning in the digital environment. A wider, collaborative exploration is needed to provide comparative studies which move beyond case studies. Impact on Society: Online learning mechanisms, such as e-tutorials, offer students different means of acquiring essential literacy skills and different ways to interact with content. E-tutorials constitute reusable learning objects, which can be accessed as just-in-time delivery modes, when students perceive they need to review particular skills or reinforce learning material. Future Research: This research is now expanding into different types of reusable learning objects. E-tutorials may be developed in multiple ways, and comparative research around e-tutorial models will deepen our understanding of how students interact with content in formal learning contexts. As the digital educational landscape continues to expand alongside traditional face-to-face and analogue learning modes, a key research focus will be student and instructor perceptions and experience of blended learning in different contexts.

Aim/Purpose: The purpose of this study is to develop an efficient methodology that can assist the evaluators in assessing a variable number of individuals that are working in groups and guarantee that the assessment is dependent on the group members’ performance and contribution to the work developed. Background: Collaborative work has been gaining more popularity in academic settings. However, group assessment needs to be performed according to each individual’s performance. The problem rests on the need to distinguish each member of the group in order to provide fair and unbiased assessments. Methodology: Design Science Research methodology supported the design of a framework able to provide the evaluator with the means to distinguish individuals in a workgroup and deliver fair results. Hevner’s DSR guidelines were fulfilled in order to describe WebAVALIA. To evaluate the framework, a quantitative study was performed and the first results are presented. Contribution: This paper provides a methodological solution regarding a fair evaluation of collaborative work through a tool that allows its users to perform their own assessment and peer assessment. These are made accordingly to the user’s perspectives on the performance of each group member throughout the work development. Findings: The first analysis of the results indicates that the developed method provides fairness in the assessment of group members, delivering a distinction amongst individuals. Therefore, each group member obtains a mark that corresponds to their specific contribution to the workgroup. Recommendations for Practitioners: For those who intend to apply this workgroup assessment method, it is relevant to raise student awareness about the methodology that is going to be used. That is, all the functionalities and steps in WebAVALIA have to be thoroughly explained before beginning of the project. Then, the evaluators have to decide about the students’ intermediate voting, namely if the evaluator chooses or not to publish student results throughout the project’s development. If there is the decision to display these intermediate results, the evaluator must try to encourage collaboration among workgroup members, instead of competition. Recommendation for Researchers: This study explores the design and development of an e-assessment tool – WebAVALIA. In order to assess its feasibility, its use in other institutions or contexts is recommended. The gathering of user opinions is suggested as well. It would then be interesting to compare the findings of this study with the results from other experimentations Impact on Society: Sometimes, people develop a rejection of collaborative work because they feel exploited due to the biased evaluation results. However, the group members assessment distinction, according to each one’s performance, may give each individual a sense of fairness and reward, leading to an openness/willingness towards collaborative work. Future Research: As future work, there are plans to implement the method in other group assessment contexts – such as sports and business environments, other higher education institutions, technical training students – in other cultures and countries. From this myriad of contexts, satisfaction results would be compared. Other future plans are to further explore the mathematical formulations and the respective WebAVALIA supporting algorithms.

Aim/Purpose: The current study was conducted to investigate the students’ perceived satisfaction with the use of a semantic-based online laboratory, which provides students with a search mechanism for laboratory resources, such as instruments and devices. Background: The increasing popularity of using online teaching labs, as an important element of experiential learning in STEM education, is because they represent a collection of integrated tools that allow students and teachers to interact and work collaboratively, whereas they provide an enriched learning content delivery mechanism. Moreover, several research studies have proposed various approaches for online teaching laboratories. However, there are hardly any studies that examine the student satisfaction provided by online laboratories based on students’ experiential learning. Methodology: To measure the effectiveness of the laboratory, we performed a case study in a Computer Fundamentals online course in which undergraduate students were able to manage devices and instruments remotely. Participants were a sample of 50 third semester students of Bachelor’s degree in Information Technology Administration who were divided in experimental and control groups (online laboratory vs. traditional manner). Given a laboratory assignment, students were able to carry out the management of devices and instruments through a LabView virtual environment and web services. The data of the experiment were collected through two questionnaires from both groups. The first is a system usability score (SUS) questionnaire concerning lab usability and the second one students’ cognitive load. Contribution: The results of the study showed a high correlation between usability and cognitive load-satisfaction of students who used the online teaching laboratory compared to the students who did not use it. Findings: On the one hand, the online laboratory provided students with an easy way to share and deploy instruments and devices, thus enhancing system usability. On the other hand, it offered important facilities which enabled students to customize the search for instruments and devices, which certainly had a positive impact on the relationship between cognitive load and satisfaction. Recommendations for Practitioners: In this work we propose an intuitive laboratory interface as well as easiness to use but challenging and capable of providing similar experiences to the traditional laboratory. Recommendation for Researchers: This study is one of the first to analyze the cognitive load-satisfaction relationship and compare it with usability scores. Impact on Society: Our analyses make an important contribution to the literature by suggesting a correlation analysis comparing the results of experimental and control groups that participated in this research work, in terms of usability and cognitive load-satisfaction. Future Research: Future work will also investigate other methodological aspects of instructional design with the aim to improve personalized learning and reinforce collaborative experiences, as well as to deal with problems related to laboratory access, such as authentication, scheduling, and interoperability.

Aim/Purpose: This study reports the outcome of how a first pilot semester introductory programming course was designed to provide tangible evidence in support of the concept of Student Ownership of Learning (SOL) and how the outcomes of this programming course facilitate effective student learning. Background: Many instructors want to create or redesign their courses to strengthen the relationship between teaching and learning; however, the researchers of this study believe that the concept of Student Ownership of Learning (SOL) connects to student engagement and achievement in the classroom setting. The researchers redesigned the introductory programming course to include valuable teaching methods to increase Student Ownership of Learning and constructive approaches such as making students design an authentic mobile app project as individuals, partners, or within teams. The high quality of students’ projects positioned them as consultants to the university IT department. Methodology: This paper employs a case study design to construct a qualitative research method as it relates to the phenomenon of the study’s goals and lived experiences of students in the redesigned introductory programming course. The redesigned course was marketed to students as a new course with detailed description and elements that were different from the traditional computer science introductory programming course requirement. The redesigned introductory programming course was offered in two sections: one section with 14 registered students and the other section with 15 registered students. One faculty member instructed both sections of the course. A total of 29 students signed up for the newly redesigned introductory programming course, more than in previous semesters, but two students dropped out within the first two weeks of the redesigned course making a total of 27 students. The redesigned coursework was divided into two parts of the semester. The first part of the semester detailed description and elements of the coursework including a redesigned approach with preparation for class, a quiz, and doing homework in class, which gives students control of decisions whenever possible; and working with each other, either with a partner or in a team. The second part of the semester focuses on students designing a non-trivial working mobile app and presenting their developing mobile app at a significant public competition at the end of the semester. Students developed significantly complex mobile apps and incorporated more complex functionality in their apps. Both Management Information System (MIS) major students and Computer Science major students were in the same course despite the fact that MIS students had never taken a programming course before; however, the Computer Science students had taken at least one course of programming. Contribution: This study provides a practical guide for faculty members in Information Technology programs and other faculty members in non-Computer Science programs to create or redesign an introductory course that increases student engagement and achievement in the classroom based on the concept of Student Ownership of Learning (SOL). This study also deepens the discussion in curriculum and instruction on the value to explore issues that departments or programs should consider when establishing coursework or academic programs. Findings: This study found two goals evidently in support to increase Student Ownership of Learning (SOL). The first goal (Increase their ownership of learning SOL) showed that students found value in the course contents and took control of their learning; therefore, the faculty no longer had to point out how important different programming concepts were. The students recognized their own learning gap and were excited when shown a programming concept that addressed the gap. For example, student comments were met with “boy, we can really use this in our app” instead of comments about how complex they were. The coursework produced a desired outcome for students as they would get the knowledge needed to make the best app that they could. The second goal (Develop a positive attitude toward the course) showed positive results as students developed a more positive attitude towards the course. Student actions in the classroom strongly reflected a positive attitude. Attendance was almost 100% during the semester even though no points for attendance were given. Further evidence of Student Ownership of Learning and self-identity was students’ extensive use of the terminology and concept of the course when talking to others, especially during the public competition. Students were also incorporating their learning into their identities. For example, teams became known by their app such as the Game team, the Recipe team, and the Parking team. One team even made team t-shirts. Another exciting reflection of the Student Ownership of Learning which occurred was the learning students did by themselves. Recommendations for Practitioners: Practitioners can share best practices with faculty in different departments, programs, universities, and educational consultants to cultivate the best solution for Student Ownership of Learning based on student engagement and achievement in the classroom setting. Recommendation for Researchers: Researchers can explore different perspectives with scholars and practitioners in various disciplinary fields of study to create or redesign courses and programs to reflect Student Ownership of Learning (SOL). Impact on Society: Student Ownership of Learning is relevant for faculty and universities to incorporate in the creation or redesigning of coursework in academic programs. Readers can gain an understanding that student engagement and achievement are two important drivers of Student Ownership of Learning (SOL) in the classroom setting. Future Research: Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different research samples and hypotheses on Student Ownership of Learning (SOL).

Aim/Purpose: In this paper, we present our experience in design and delivery of a graduate Information Systems Management (ISM) course in an online MBA program. Also presented are a detailed examination of the design and delivery of the online course, survey results of students’ perceptions and backgrounds, course evaluation results, best practices and lessons learned, and potential changes and future actions. Background: This graduate ISM course needs to not only cover a broad range of dynamic technology and business topics, but also strike a balance between the width and depth of the content. Effective course design and delivery are critical to improved teaching and learning, especially when the course is delivered online. Methodology: We provided a comprehensive review of the related literature to develop guidelines for the design and delivery of our ISM course; we collected survey data to evaluate the students’ backgrounds and their perceptions of the course; we used data analysis and content analysis methods to assess the course evaluation results. Contribution: A review of the related literature indicates that IS researchers and educators have not adequately studied online graduate education. Given the importance of the graduate ISM course in most MBA programs, and the lack of attention from the IS community, it is critical to address this gap in the research. We believe we have done so with this paper. Findings: The paper’s major findings are embedded in a detailed examination of the design and delivery of the online course, survey results of students’ perceptions and backgrounds, course evaluation results, best practices and lessons learned, and potential changes and future actions. Recommendations for Practitioners: Even though our experience may not be fully applicable to other institutions, we hope our IS colleagues can learn from the design and delivery of this online course, as well as our best practices and lessons learned to improve the teaching and learning effectiveness in IS online graduate education, in general. Furthermore, we provide instructors with an actionable framework onto which they can map their current course offering, and compare their current pedagogical offering to literature driven best practices for ISM courses, in particular. Recommendation for Researchers: It is our hope that the design and delivery of this online course, and our best practices and lessons learned can inspire our IS colleagues to search for innovative ways to improve the teaching and learning effectiveness in IS online graduate education. In addition, we distill a literature driven framework for ISM courses design and delivery that can help researchers frame their pedagogical research questions. Impact on Society: The online course in this study prepares students for more efficiently and effectively delivering IT systems in organizations. Many MBA students work for non-profits and other socially-focused organizations and are able to use the skills learned in the course for the betterment of society. Future Research: We will continue to monitor the impact of the changes on student learning effectiveness and attempt to identify additional innovative ways to improve the design and delivery of this online ISM course.

Aim/Purpose: The aim of this study is to understand student’s opinions and perceptions about e-assessment when the assessment process was changed from the traditional computer assisted method to a multiple-choice Moodle based method. Background: In order to implement continuous assessment to a large number of students, several shifts are necessary, which implies as many different tests as the number of shifts required. Consequently, it is difficult to ensure homogeneity through the different tests and a huge amount of grading time is needed. These problems related to the traditional assessment based on computer assisted tests, lead to a re-design of the assessment resulting in the use of multiple-choice Moodle tests. Methodology: A longitudinal, concurrent, mixed method study was implemented over a five-year period. A survey was developed and carried out by 815 undergraduate students who experienced the electronic multiple-choice questions (eMCQ) assessment in the courses of the IS department. Qualitative analyses included open-ended survey responses and interviews with repeating students in the first year. Contribution: This study provides a reflection tool on how to incorporate frequent moments of assessment in courses with a high number of students without overloading teachers with a huge workload. The research analysed the efficiency of assessing non-theoretical topics using eMCQ, while ensuring the homogeneity of assessment tests, which needs to be complemented with other assessment methods in order to assure that students develop and acquire the expected skills and competencies. Findings: The students involved in the study appreciate the online multiple-choice quiz assessment method and perceive it as fair but have a contradictory opinion regarding the preference of the assessment method, throughout the years. These changes in perception may be related to the improvement of the question bank and categorisation of questions according to difficulty level, which lead to the nullification of the ‘luck factor’. Other major findings are that although the online multiple-choice quizzes are used with success in the assessment of theoretical topics, the same is not in evidence regarding practical topics. Therefore, this assessment needs to be complemented with other methods in order to achieve the expected learning outcomes. Recommendations for Practitioners: In order to be able to evaluate the same expected learning outcomes in practical topics, particularly in technology and information systems subjects, the evaluator should complement the online multiple-choice quiz assessment with other approaches, such as a PBL method, homework assignments, and/or other tasks performed during the semester. Recommendation for Researchers: This study explores e-assessment with online multiple-choice quizzes in higher education. It provides a survey that can be applied in other institutions that are also using online multiple-choice quizzes to assess non-theorical topics. In order to better understand the students’ opinions on the development of skills and competencies with online multiple-choice quizzes and on the other hand with classical computer assisted assessment, it would be necessary to add questions concerning these aspects. It would then be interesting to compare the findings of this study with the results from other institutions. Impact on Society: The increasing number of students in higher education has led to a raised use of e-assessment activities, since it can provide a fast and efficient manner to assess a high number of students. Therefore, this research provides meaningful insight of the stakeholders’ perceptions of online multiple-choice quizzes about practical topics. Future Research: An interesting study, in the future, would be to obtain the opinions of a particular set of students on two tests, one of the tests using online multiple-choice quizzes and the other through a classical computer assisted assessment method. A natural extension of the present study is a comparative analysis regarding the grades obtained by students who performed one or another type of assessment (online multiple-choice quizzes vs. classical computer assisted assessment).

Aim/Purpose: This study aimed to reveal the effect of the previous Internet-based education (IBE) experiences of the students’ readiness, attitude, and self-control / self-management variables towards the e-learning process, and also to determine their opinions. Background: The institutions have made efforts to ensure the continuity of education through their learning management systems and the necessity of addressing the e-learning process from the perspective of students once again showed itself as an undeniable fact. Accordingly, the necessity to consider holistically the variables of readiness, attitude, and self-control/self-management, which affect students’ adaptation to e-learning process, has once again emerged based on the relevant literature. Methodology: This research based on the simultaneous mixed method considering the previous IBE experiences of 75 Computer Education and Instructional Technology (CEIT) students taking part in the study in Turkey. The quantitative results of the study were analyzed based on the single-group pretest-posttest weak experimental design. Qualitative results were obtained through the structured interview form and set an example for the case study. Contribution: The results showed that regardless of students’ previous Internet-based education (IBE) experience, it is seen that increasing and continuous experience has a significant effect on the readiness, attitude and self-control / self-management variables towards the e-learning process. The main contribution of experimental results showed that IBE experience is effective on individuals’ perceptions of internet self-efficacy, and has an impact on the self-learning skills of individuals. In addition to this, the e-learning experience has an impact on individuals’ self-evaluation. It is also seen that the certificate presented to learners in the e-learning environment has a positive effect on students’ attitudes towards e-learning processes. Finally, the experiences of e-learning processes, the methods used to transfer the content in the learning environment, the motivation and feedback provided to the learner also support the significant difference obtained in terms of readiness, attitude and self-control / self-management. Findings: After the findings were analyzed holistically in depth, it has been observed that; if the contents offered to students in e-learning environments support their professional development, in this case, their attitudes, readiness (excluding the sub-dimension of learner control), and self-control/self-management skills for these environments differ significantly in the posttest. It is also among the results that students having previous IBE experience have not higher awareness levels on online communication self-efficacy, technology use self-efficacy, readiness for e-learning, e-learning predisposition, self-reinforcement, self-control management, although significantly found. The findings regarding the effectiveness of the experimental process are as follows: Although it is possible for the students having previous IBE experience to use these experiences within the course for their personal development, it has been seen that the observed differences regarding students’ readiness, attitude, and self-control/self-management towards e-learning processes arise from the experimental operation. Recommendations for Practitioners: It is recommended for the policy-makers and practitioners that while e-learning platforms were designing, using different methods for delivering the content is as important as making the interaction meaningful and sustainable. In addition to this, to develop a positive attitude it is recommended that individuals’ participation of an e-learning platform should be supported with a certificate. Recommendation for Researchers: Researchers should test the obtained results by a well-structured e-learning platform with their recorded activities on the platform (e.g. in which section was used mostly by a learner etc.). Hence, the impact of IBE experiences might be discussed in an up level framework. Impact on Society: Actually, this study is based on a mix design and the results were also meaningful especially considering the implacable global pandemic. It is clearly understood by this process that e-learning is very important. In line with this, to support the e-learning process (e.g. with the method while delivering the content, well-structured feedback, motivation strategies etc.) and make it sustainable, the increasing of individual’s readiness, attitude, and self-control through the IBE would be indispensable. Future Research: Future studies might focus on the longitudinal methods. It is worth to find out how the students experiences affect the sustainability of the course content, and what should the program developer make to improve their course content in line with the findings of longitudinal studies.

Aim/Purpose: The purpose of this paper is to develop and evaluate a debiasing-based approach to assessing the learning materials in problem-based learning (PBL) environments. Background: Research in cognitive debiasing suggests nine debiasing strategies improve decision-making. Given the large number of decisions made in semester-long, problem-based learning projects, multiple tools and techniques help students make decisions. However, instructors may struggle to identify the specific tools or techniques that could be modified to best improve students’ decision-making in the project. Furthermore, a structured approach for identifying these modifications is lacking. Such an approach would match the debiasing strategies with the tools and techniques. Methodology: This debiasing framework for the PBL environment is developed through a study of debiasing literature and applied within an e-commerce course using the Model for Improvement, continuous improvement process, as an illustrative case to show its potential. In addition, a survey of the students, archival information, and participant observation provided feedback on the debiasing framework and its ability to assess the tools and techniques within the PBL environment. Contribution: This paper demonstrates how debiasing theory can be used within a continuous improvement process for PBL courses. By focusing on a cognitive debiasing-based approach, this debiasing framework helps instructors 1) identify what tools and techniques to change in an PBL environment, and 2) assess which tools and techniques failed to debias the students adequately, providing potential changes for future cycles. Findings: Using the debiasing framework in an e-commerce course with significant PBL elements provides evidence that this framework can be used within IS courses and more broadly. In this particular case, the change identified in a prior cycle proved effective and additional issues were identified for improvement. Recommendations for Practitioners: With the growing usage of semester-long PBL projects in business schools, instructors need to ensure that their design of the projects incorporates techniques that improve student learning and decision making. This approach provides a means for assessing the quality of that design. Recommendation for Researchers: This study uses debiasing theory to improve course techniques. Researchers interested in assessment, course improvement, and program improvement should incorporate debiasing theory within PBL environments or other types of decision-making scenarios. Impact on Society: Increased awareness of cognitive biases can help instructors, students, and professionals make better decisions and recommendations. By developing a framework for evaluating cognitive debiasing strategies, we help instructors improve projects that prepare students for complex and multifaceted real-world projects. Future Research: The approach could be applied to multiple contexts, within other courses, and more widely within information systems to extend this research. The framework might also be refined to make it more concise, integrated with assessment, or usable in more contexts.

Aim/Purpose: During the education of future engineers and experts in the field of computer science and information communication technology, the achievement of learning outcomes related to different levels of cognitive ability and knowledge dimensions can be a challenge. Background: Teachers need to design an appropriate set of activities for students and combine theory-based knowledge acquisition with practical training in technical skills. Including various activities for formative assessment during the course can positively affect students’ motivation for learning and ensure appropriate and timely feedback that will guide students in further learning. Methodology: The aim of the research presented in this paper is to propose an approach for course delivery in the field of software engineering and to determine whether the use of the approach increases student’s academic achievement. Using the proposed approach, the course Process Modeling for undergraduate students was redesigned and experimental study was conducted. Course results of the students (N=82) who took the new version of the course (experimental group) were compared to the results of the students from the control group (N=66). Contribution: An approach for a blended learning course in the field of software engineering was developed. This approach is based on the formative assessment activities that promote collaboration and the use of digital tools. Newly designed activities are used to encourage a greater level of acquired theoretical content and enhance the acquisition of subject-specific skills needed for practical tasks. Findings: The results showed that students who participated in the formative assessment activities achieved significantly better results. They had significantly higher scores in the main components of assessment compared to the students from the control group. In addition, students from the experimental group expressed positive views about the effectiveness of the used approach. Recommendations for Practitioners: The proposed approach has potential to increase students’ motivation and academic achievements so practitioners should consider to apply it in their own context. Recommendation for Researchers: Researchers are encouraged to conduct additional studies to explore the effectiveness of the approach with different courses and participants as well as to provide further insights regarding its applicability and acceptance by students. Impact on Society: The paper provides an approach and an example of good practice that may be beneficial for the university teachers in the field of computer science, information-communication technology, and engineering. Future Research: In the future, face-to-face activities will be adapted for performance in an online environment. Future work will also include a research on the possibilities of personalization of activities in accordance with the students’ characteristics.

Aim/Purpose: Business analytics is a cross-functional field that is important to implement for a college and has emerged as a critically important core component of the business curriculum. It is a difficult task due to scheduling concerns and limits to faculty and student resources. This paper describes the process of creating a central video repository to serve as a platform for just in time teaching and the impact on student learning outcomes. Background: Industry demand for employees with analytical knowledge, skills, and abilities requires additional analytical content throughout the college of business curriculum. This demand needs other content to be added to ensure that students have the prerequisite skills to complete assignments. Two pedagogical approaches to address this issue are Just-in-Time Teaching (JiTT) and scaffolding, grounded in the Vygoskian concept of “Zone of Proximal Development. Methodology: This paper presents a case study that applies scaffolding and JiTT teaching to create a video repository to add business analytics instruction to a curriculum. The California Critical Thinking Skills Test (CCTST) and Major Field Test (MFT) scores were analyzed to assess learning outcomes. Student and faculty comments were considered to inform the results of the review. Contribution: This paper demonstrates a practical application of scaffolding and JiTT theory by outlining the process of using a video library to provide valuable instructional resources that support meaningful learning, promote student academic achievement, and improve program flexibility. Findings: A centrally created library is a simple and inexpensive way to provide business analytics course content, augmenting standard content delivery. Assessment of learning scores showed an improvement, and a summary of lessons learned is provided to guide implications. Recommendations for Practitioners: Pedagogical implications of this research include the observation that producing a central library of instructor created videos and assignments can help address knowledge and skills gaps, augment the learning of business analytics content, and provide a valuable educational resource throughout the college of business curriculum. Recommendation for Researchers: This paper examines the use of scaffolding and JiTT theories. Additional examination of these theories may improve the understanding and limits of these concepts as higher education evolves due to the combination of market forces changing the execution of course delivery. Impact on Society: Universities are tasked with providing new and increasing skills to students while controlling the costs. A centrally created library of instructional videos provides a means of delivering meaningful content while controlling costs. Future Research: Future research may examine student success, including the immediate impact of videos and longitudinally using video repositories throughout the curriculum. Studies examining the approach across multiple institutions may help to evaluate the success of video repositories. Faculty acceptance of centrally created video libraries and assignments should be considered for the value of faculty recruiting and use in the classroom. The economic impact on both the university and students should be evaluated.

Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated subjectively using a rubric for years. Subjective assessments are simple to construct yet inconsistent and biased to evaluate. Objective assessments are stable, reliable, and easy to conduct. However, they usually lack rubrics. Methodology: In this study, a Top-Down assessment approach is followed, i.e., a rubric focused on the learning outcome of the subject is designed, and the proficiency of learners is judged by their performance in conducting the task given. A JAVA rubric is proposed based on the learning outcomes like syntactical, logical, conceptual, and advanced JAVA skills. A JAVA objective quiz (with multiple correct options) is prepared based on the rubric criteria, comprising five questions per criterion. The examination was conducted for 209 students (100 from the MCA course and 109 from B.Tech. course). The suggested rubric was used to compute the results. K-means clustering was applied to the results to classify the students according to their learning preferences and abilities. Contribution: This work contributes to the field of rubric designing by creating an objective programming assessment and analyzing the learners’ performance using machine learning techniques. It also facilitates a reliable feedback approach offering various possibilities in student learning analytics. Findings: The designed rubric, partial scoring, and cluster analysis of the results help us to provide individual feedback and also, group the students based on their learning skills. Like on average, learners are good at remembering the syntax and concepts, mediocre in logical and critical thinking, and need more practice in code optimization and designing applications. Recommendations for Practitioners: The practical implications of this work include rubric designing for objective assessments and building an informative feedback process. Faculty can use this approach as an alternative assessment measure. They are the strong pillars of e-assessments and virtual learning platforms. Recommendation for Researchers: This research presents a novel approach to rubric-based objective assessments. Thus, it provides a fresh perspective to the researchers promising enough opportunities in the current era of digital education. Impact on Society: In order to accomplish the shared objective of reflective learning, the grading rubric and its accompanying analysis can be utilized by both instructors and students. As an instructional assessment tool, the rubric helps instructors to align their pedagogies with the students’ learning levels and assists students in updating their learning paths based on the informative topic-wise scores generated with the help of the rubric. Future Research: The designed rubric in this study can be extended to other programming languages and subjects. Further, an adaptable weighted rubric can be created to execute a flexible and reflective learning process. In addition, outcome-based learning can be achieved by measuring and analyzing student improvements after rubric evaluation.

Aim/Purpose: To encourage students’ engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems – a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their work. This process is widely applied as a learning method to involve students in the progress of their learning. However, as students have different ability levels, the efficacy of the peer feedback differs from case to case. Thus, peer assessment may not provide satisfactory results for students. In order to mitigate this issue, this paper explains and evaluates an algorithm that matches the author to a set of reviewers. The technique matches authors and reviewers based on how difficult the authors perceived the assignment to be, and the algorithm then matches the selected author to a group of reviewers who may meet the author’s needs in regard to the selected assignment. Methodology: This study used the Multiple Criteria Decision-Making methodology (MCDM) to determine a set of reviewers from among the many available options. The weighted sum method was used because the data that have been collected in user profiles are expressed in the same unit. This study produced an experimental result, examining the algorithm with a real collected dataset and mock-up dataset. In total, there were 240 students in the real dataset, and it contained self-assessment scores, peer scores, and instructor scores for the same assignment. The mock-up dataset created 1000 records for self-assessment scores. The algorithm was evaluated using focus group discussions with 29 programming students and interviews with seven programming instructors. Contribution: This paper contributes to the field in the following two ways. First, an algorithm using a MCDM methodology was proposed to match authors and reviewers in order to facilitate the peer assessment process. In addition, the algorithm used self-assessment as an initial data source to match users, rather than randomly creating reviewer – author pairs. Findings: The findings show the accurate results of the algorithm in matching three reviewers for each author. Furthermore, the algorithm was evaluated based on students’ and instructors’ perspectives. The results are very promising, as they depict a high level of satisfaction for the Balanced Allocation algorithm. Recommendations for Practitioners: We recommend instructors to consider using the Balanced Allocation algorithm to match students in peer assessments, and consequently to benefit from personalizing peer assessment based on students' needs. Recommendation for Researchers: Several MCDM methods could be expanded upon, such as the analytic hierarchy process (AHP) if different attributes are collected, or the artificial neural network (ANN) if fuzzy data is available in the user profile. Each method is suitable for special cases depending on the data available for decision-making. Impact on Society: Suitable pairing in peer assessment would increase the credibility of the peer assessment process and encourage students’ engagement in peer assessments. Future Research: The Balanced Allocation algorithm could be applied using a single group, and a peer assessment with random matching with another group may also be conducted, followed by performing a t-test to determine the impact of matching on students’ performances in the peer assessment activity.

Aim/Purpose: The purpose of this research is to determine whether ESL teaching videos as a form of asynchronous online knowledge sharing can act as an aid to ESL learners internalizing knowledge in language acquisition. In this context, internalizing knowledge carries the meaning of being able to remember language, and purposefully and accurately use it context, including appropriacy of language, and aspects of correct pronunciation, intonation, stress patterns and connected speech, these being the elements of teaching and practice that are very often lacking in asynchronous, online, instructional video. Background: Knowledge Management is the field of study, and the practice, of discovering, capturing, sharing, and applying knowledge, typically with a view to translating individuals’ knowledge into organizational knowledge. In the field of education, it is the sharing of instructors’ knowledge for students to be able to learn and usefully apply that knowledge. In recent pandemic times, however, the mode of instruction has, of necessity, transitioned from face-to-face learning to an online environment, transforming the face of education as we know it. While this mode of instruction and knowledge sharing has many advantages for the online learner, in both synchronous and asynchronous learning environments, it presents certain challenges for language learners due to the absence of interaction and corrective feedback that needs to take place for learners of English as a Second Language (ESL) to master language acquisition. Unlike other subjects where the learner has recourse to online resources to reinforce learning through referencing external information, such as facts, figures, or theories, to be successful in learning a second language, the ESL learner needs to be able to learn to process thought and speech in that language; essentially, they need to learn to think in another language, which takes time and practice. Methodology: The research employs a systematic literature review (SLR) to determine the scope and extent to which the subject is covered by existing research in this field, and the findings thereof. Contribution: Whilst inconclusive in relation to internalizing language through online, asynchronous instructional video, through its exploratory nature, the research contributes towards the body of knowledge in online learning through the drawing together of various studies in the field of learning through asynchronous video through improving video and instructional quality. Findings: The findings of the systematic literature review revealed that there is negligible research in this area, and while information exists on blended and flipped modes of online learning, and ways to improve the quality and delivery of instructional video generally, no prior research on the exclusive use of asynchronous videos as an aid to internalizing English as a second language were found. Recommendations for Practitioners: From this research, it is apparent that there is considerably more that practitioners can do to improve the quality of instructional videos that can help students engage with the learning, from which students stand a much better chance of internalizing the learning. Recommendation for Researchers: For researchers, the absence of existing research is an exciting opportunity to further explore this field. Impact on Society: Online learning is now globally endemic, but it poses specific challenges in the field of second language learning, so the development of instructional videos that can facilitate this represents a clear benefit to all ESL learners in society as a whole. Future Research: Clearly the absence of existing research into whether online asynchronous instructional videos can act as an aid to internalizing the acquisition of English as a second language would indicate that this very specific field is one that merits future research. Indeed, it is one that the author intends to exploit through primary data collection from the production of a series of asynchronous, online, instructional videos.

Aim/Purpose: This paper proposes a new approach to developing a deep learning-based prototyping wearable model which can assist blind and visually disabled people to recognize their environments and navigate through them. As a result, visually impaired people will be able to manage day-to-day activities and navigate through the world around them more easily. Background: In recent decades, the development of navigational devices has posed challenges for researchers to design smart guidance systems for visually impaired and blind individuals in navigating through known or unknown environments. Efforts need to be made to analyze the existing research from a historical perspective. Early studies of electronic travel aids should be integrated with the use of assistive technology-based artificial vision models for visually impaired persons. Methodology: This paper is an advancement of our previous research work, where we performed a sensor-based navigation system. In this research, the navigation of the visually disabled person is carried out with a vision-based 3D-designed wearable model and a vision-based smart stick. The wearable model used a neural network-based You Only Look Once (YOLO) algorithm to detect the course of the navigational path which is augmented by a GPS-based smart Stick. Over 100 images of each of the three classes, namely straight path, left path and right path, are being trained using supervised learning. The model accurately predicts a straight path with 79% mean average precision (mAP), the right path with 83% mAP, and the left path with 85% mAP. The average accuracy of the wearable model is 82.33% and that of the smart stick is 96.14% which combined gives an overall accuracy of 89.24%. Contribution: This research contributes to the design of a low-cost navigational standalone system that will be handy to use and help people to navigate safely in real-time scenarios. The challenging self-built dataset of various paths is generated and transfer learning is performed on the YOLO-v5 model after augmentation and manual annotation. To analyze and evaluate the model, various metrics, such as model losses, recall value, precision, and maP, are used. Findings: These were the main findings of the study: • To detect objects, the deep learning model uses a higher version of YOLO, i.e., a YOLOv5 detector, that may help those with visual im-pairments to improve their quality of navigational mobilities in known or unknown environments. • The developed standalone model has an option to be integrated into any other assistive applications like Electronic Travel Aids (ETAs) • It is the single neural network technology that allows the model to achieve high levels of detection accuracy of around 0.823 mAP with a custom dataset as compared to 0.895 with the COCO dataset. Due to its lightning-speed of 45 FPS object detection technology, it has become popular. Recommendations for Practitioners: Practitioners can help the model’s efficiency by increasing the sample size and classes used in training the model. Recommendation for Researchers: To detect objects in an image or live cam, there are various algorithms, e.g., R-CNN, Retina Net, Single Shot Detector (SSD), YOLO. Researchers can choose to use the YOLO version owing to its superior performance. Moreover, one of the YOLO versions, YOLOv5, outperforms its other versions such as YOLOv3 and YOLOv4 in terms of speed and accuracy. Impact on Society: We discuss new low-cost technologies that enable visually impaired people to navigate effectively in indoor environments. Future Research: The future of deep learning could incorporate recurrent neural networks on a larger set of data with special AI-based processors to avoid latency.

Aim/Purpose: The goal of the study was to examine the perceptions of senior academic staff who also serve as policymakers in Israeli colleges of education, regarding the integration of technology in teacher education, and the shift to online learning during the Covid-19 pandemic. There is little research on this issue and consequently, the aim of the present study is to fill this lacuna. Background: In Israel, senior academic staff in colleges of education play a particularly important role in formulating institutional policies and vision regarding the training of preservice teachers. They fulfil administrative functions, teach, and engage in research as part of their academic position. During the Covid-19, they led the shift to online learning. However, there is little research on their perceptions of technology integration in teacher education in general, and during the Covid-19, in particular. Methodology: This qualitative study conducted semi-structured interviews with 25 senior academic staff from 13 academic colleges of education in Israel. Contribution: The study has practical implications for the implementation of technology in teacher education, suggesting the importance of establishing open discourse and collaboration between college stakeholders to enable enactment of a vision for equity-that allows programs to move swiftly from crisis-management to innovation and transformation during the Covid-19 pandemic. Findings: The findings obtained from content analysis of the interviews reveals a central concept: “On both sides of the divide”, and points of intersection in the perceptions of the senior academic staff. The central concept encompassed three themes: (1) centralization - between top-down and bottom-up policies, (2) between innovation and conservation, and (3) between crisis and growth. The findings indicate that in times of crisis, the polarity surrounding issues essential to the organisation’s operation is reduced, and a blend is formed to create a new reality in which the various dichotomies merge. Recommendations for Practitioners: The study has practical implications for the scope of discussions on the implementation of technology in teacher education (formulating a vision and policies, and their translation into practice), suggesting that such discussions should consider the perceptions of policymakers. Recommendation for Researchers: The findings reflect the challenges faced by senior academic staff at colleges of education that reflect the ongoing attempts to negotiate and reconcile different concerns. Impact on Society: The findings have implications for colleges of education that are responsible for pre-service teachers' teaching practices. Future Research: An enacted vision for equity-based educator preparation that allows programs to move swiftly from crisis-management to innovation and transformation. Future research might reveal a more complete picture by investigating a broader spectrum of stakeholders both in Israel and elsewhere. Hence, future research should examine the power relations between senior college staff and external bodies such as the Higher Education Council (which determines higher education policies in Israel).

Aim/Purpose: This paper presents a machine learning approach for analyzing Course Learning Outcomes (CLOs). The aim of this study is to find a model that can check whether a CLO is well written or not. Background: The use of machine learning algorithms has been, since many years, a prominent solution to predict learner performance in Outcome Based Education. However, the CLOs definition is still presenting a big handicap for faculties. There is a lack of supported tools and models that permit to predict whether a CLO is well written or not. Consequently, educators need an expert in quality and education to validate the outcomes of their courses. Methodology: A novel method named CLOCML (Course Learning Outcome Classification using Machine Learning) is proposed in this paper to develop predictive models for CLOs paraphrasing. A new dataset entitled CLOC (Course Learning Outcomes Classes) for that purpose has been collected and then undergone a pre-processing phase. We compared the performance of 4 models for predicting a CLO classification. Those models are Support Vector Machine (SVM), Random Forest, Naive Bayes and XGBoost. Contribution: The application of CLOCML may help faculties to make well-defined CLOs and then correct CLOs' measures in order to improve the quality of education addressed to their students. Findings: The best classification model was SVM. It was able to detect the CLO class with an accuracy of 83%. Recommendations for Practitioners: We would recommend both faculties’ members and quality reviewers to make an informed decision about the nature of a given course outcome. Recommendation for Researchers: We would highly endorse that the researchers apply more machine learning models for CLOs of various disciplines and compare between them. We would also recommend that future studies investigate on the importance of the definition of CLOs and its impact on the credibility of Key Performance Indicators (KPIs) values during accreditation process. Impact on Society: The findings of this study confirm the results of several other researchers who use machine learning in outcome-based education. The definition of right CLOs will help the student to get an idea about the performances that will be measured at the end of a course. Moreover, each faculty can take appropriate actions and suggest suitable recommendations after right performance measures in order to improve the quality of his course. Future Research: Future research can be improved by using a larger dataset. It could also be improved with deep learning models to reach more accurate results. Indeed, a strategy for checking CLOs overlaps could be integrated.

Aim/Purpose: This research aims to describe layering of career-like experiences over existing curriculum to improve perceived educational value. Background: Feedback from students and regional businesses showed a clear need to increase student’s exposure to career-like software development projects. The initial goal was to develop an instructor-optional project that could be used in a single mid-level programming course; however, the pilot quickly morphed into a multi-year study examining the feasibility of agile projects in a variety of settings. Methodology: Over the course of four years, an agile project was honed through repeated Design Based Research (DBR) cycles of design, implementation, testing, communication, and reflective analysis. As is common with DBR, this study did not follow single methodology design; instead, analysis of data coupled with review of literature led to exploration and testing of a variety of methodologies. The review phase of each cycle included examination of best practices and methodologies as determined by analysis of oral and written comments, weekly journals, instructor feedback, and surveys. As a result of participant feedback, the original project was expanded to a second project, which was tested in another Software Engineering (SE) course. The project included review and testing of many academic and professional methodologies, such as Student Ownership of Learning, Flipped Classroom, active learning, waterfall, agile, Scrum, and Kanban. The study was homogenous and quasi-experimental as the population consisted solely of software engineering majors taking required courses; as based on validity of homogenous studies, class sizes were small, ranging from 8 to 20 students. Close interactions between respondents and the instructor provided interview-like settings and immersive data capture in a natural environment. Further, the iterative development practices of DBR cycles, along with the inclusion of participants as active and valued stakeholders, was seen to align well with software development practitioner practices broadly known as agile. Contribution: This study is among the first to examine layering a career-like software development project on top of a course through alteration of traditional delivery, agile development, and without supplanting existing material. Findings: In response to industry recommendations for additional career-like experiences, a standalone agile capstone-like project was designed that could be layered over an existing course. Pilot data reflected positive perceptions of the project, although students did not have enough time to develop a working prototype in addition to completing existing course materials. Participant feedback led to simultaneous development of a second, similar project. DBR examination of both projects resulted in a simplified design and the ability to develop a working prototype, if and only if the instructor was willing to make adjustments to delivery. After four years, a solution was developed that is both stable and flexible. The solution met the original charge in that it required course delivery, not course material, to be adjusted. It is critical to note that when a working prototype is desired, a portion of the lecture should be flipped allowing more time for guided instruction through project-focused active learning and study group requirements. The results support agile for standalone software development projects, as long as passive delivery methods are correspondingly reduced. Recommendations for Practitioners: Based on the findings, implementation of a career-like software development project can be well received as long as active learning components are also developed. Multiple cycles of DBR are recommended if future researchers wish to customize instructional delivery and develop complex software development projects. Programming instructors are recommended to explore hybrid delivery to support development of agile career-like experiences. Small class sizes allowed the researchers to maintain an interview-like setting throughout the study and future studies with larger classes are recommended to include additional subject matter experts such as graduate students as interaction with a subject matter expert was highly valued by students. Recommendation for Researchers: Researchers are recommended to further examine career-like software development experiences that combine active learning with agile methods; more studies following agile and active learning are needed to address the challenges faced when complex software development is taught in academic settings. Further testing of standalone agile project development has now occurred in medium sized in person classes, online classes, independent studies, and creative works research settings; however, further research is needed. Future research should also examine the implementation of agile projects in larger class sizes. Increasing class size should be coupled with additional subject matter experts such as graduate students. Impact on Society: This study addresses professional recommendations for development of agile career-like experiences at the undergraduate level. This study provides empirical evidence of programming projects that can be layered over existing curriculum, with no additional cost to the students. Initial feedback from local businesses and graduates, regarding agile projects with active learning, has been positive. The area business that refused to hire our underprepared SE graduates has now hired several. Future Research: Future research should explore layering agile projects over a broader range of software development courses. Feedback from hiring professionals and former students has been positive. It is also recommended that DBR be used to develop career-like experiences for online programming courses.

Aim/Purpose: The complexity of today’s organizational databases highlights the importance of hard technical skills as well as soft skills including teamwork, communication, and problem-solving. Therefore, when teaching students about databases it follows that using a team approach would be useful. Background: Team-based learning (TBL) has been developed and tested as an instructional strategy that leverages learning in small groups in order to achieve increased overall effectiveness. This research studies the impact of utilizing team-based learning strategies in an undergraduate Database Management course in order to determine if the methodology is effective for student learning related to database technology concepts in addition to student preparation for working in database teams. Methodology: In this study, a team-based learning strategy is implemented in an undergraduate Database Management course over the course of two semesters. Students were assessed both individually and in teams in order to see if students were able to effectively learn and apply course concepts on their own and in collaboration with their team. Quantitative and qualitative data was collected and analyzed in order to determine if the team approach improved learning effectiveness and allowed for soft skills development. The results from this study are compared to previous semesters when team-based learning was not adopted. Additionally, student perceptions and feedback are captured. Contribution: This research contributes to the literature on database education and team-based learning and presents a team-based learning process for faculty looking to adopt this methodology in their database courses. This research contributes by showing how the collaborative assessment aspect of team-based learning can provide a solution for the conceptual and collaborative needs of database education. Findings: Findings related to student learning and perceptions are presented illustrating that team-based learning can lead to improvements in performance and provides a solution for the conceptual and collaborative needs of database education. Specifically, the findings do show that team scores were significantly higher than individual scores when completing class assessments. Student perceptions of both their team members and the team-based learning process were overall positive with a notable difference related to the perception of team preparedness based on gender. Recommendations for Practitioners: Educational implications highlight the challenges of team-based learning for assessment (e.g., gender differences in perceptions of team preparedness), as well as the benefits (e.g., development of soft skills including teamwork and communication). Recommendation for Researchers: This study provides research implications supporting the study of team assessment techniques for learning and engagement in the context of database education. Impact on Society: Faculty looking to develop student skills in relation to database concepts and application as well as in relation to teamwork and communication may find value in this approach, ultimately benefiting students, employers, and society. Future Research: Future research may examine the methodology from this study in different contexts as well as explore different strategies for group assignments, room layout, and the impact of an online environment.

Aim/Purpose: The purpose of this article is to provide an overview and analysis of the emerging research landscape surrounding the integration of ChatGPT into education. The main problem appears to be that this is a new, rapidly developing research area for which there is no comprehensive synthesis of the current literature. The aim of the article is to fill this gap by conducting a timely bibliometric study to map publication trends, influential works, themes, and opportunities, thus representing the growth and structure of ChatGPT educational research. Background: This article addresses the issue of the lack of a comprehensive synthesis of the new research on ChatGPT in education by conducting a bibliometric analysis. Specifically, the authors use statistical and network analysis techniques to examine the patterns of publication, citation, and keywords and map the growth, contributions, themes, structure, and opportunities in this evolving field. The bibliometric approach provides a comprehensive, evidence-based overview of the current state of the literature to uncover trends and gaps and help researchers improve their understanding of appropriate and effective applications of ChatGPT in educational contexts. Methodology: The authors used bibliometric analysis as the primary method to summarize the new research on ChatGPT in education. We searched the database of the Web of Science Core Collection to find 51 relevant documents from 2023 that included ChatGPT in the title and were classified as ‘educational research.’ The sample consisted of these 51 documents, including articles, early access articles, editorials, reviews, and letters. Statistical techniques examined publication, citation, and keyword patterns. Network analysis visualized citation and co-occurrence networks to reveal intellectual structure. The multifaceted bibliometric approach allowed a comprehensive study of the sample from a productive, conceptual, and intellectual perspective. Contribution: This article conducts comprehensive bibliometric analysis of this emerging research area and synthesizes publication, citation, and keyword data to map the growth and structure of the literature. The results reveal important trends, such as the rapid growth of publications since the release of ChatGPT, initial authorship patterns, the focus on higher education applications, and distinct research clusters around pedagogical, ethical, and assessment issues. Visualizing citation networks identifies seminal studies while mapping co-occurrence clarifies conceptual relationships between topics. The comparative analysis highlights the differences between document types, topics, and time periods. Knowledge mapping highlights gaps in the literature, such as lack of focus on K-12 contexts, and highlights opportunities for further research. Findings: Key findings from this bibliometric analysis of the emerging research land-scape surrounding ChatGPT integration in education include the following: • Since ChatGPT was released in late 2022, the number of releases has increased significantly, indicating rapid growth in this emerging space. • The most cited authors initially came primarily from Anthropic, but over time, the citations spread throughout the research community. • The topics focused primarily on higher education applications, with a clear focus on pedagogical strategies, ethical risks, and implications for assessment. • Citation networks visualized seminal studies, while the co-occurrence of keywords clarified conceptual connections. • Gaps such as applications in the K-12 context were uncovered, and opportunities for further research were highlighted. • The literature is rapidly evolving and requires ongoing monitoring of the development of this field. In general, the analysis presents the productivity, contributors, themes, struc-ture, and opportunities in this emerging area around the integration of ChatGPT in education based on current scientific evidence. The key findings focus on the growing early interest, gaps and developments that can provide insight for researchers and educators. Recommendations for Practitioners: Practitioners should carefully integrate ChatGPT into education based on new evidence, carefully assess contextual applicability, and proactively develop guidelines for ethical and equitable implementation. Ongoing advice, impact monitoring, and research partnerships are crucial to informing best practices. Educators must be vigilant for risks such as privacy, student well-being, and competence impairment while staying abreast of advances in knowledge to dynamically adapt integration strategies. The introduction should empower diverse learners through measured, integrative approaches based on continuous contextual analysis and ethical principles. Recommendation for Researchers: This article recommends that researchers conduct more studies in under-researched contexts, use multiple methods to capture nuanced impacts, increase focus on responsible integration strategies, develop tailored assessments, conduct interdisciplinary collaborations, monitor long-term adoption, mix with interactive explain and publish open access technologies, help guide adoption pathways through actionable studies, and synthesize the exponentially growing literature through updated systematic reviews. Impact on Society: The rapid publication growth and prevailing optimism suggest that the integration of ChatGPT into education will accelerate, increasing the need for rigorous research that guides ethical, responsible innovations that avoid risks and improve outcomes in all educational contexts. The findings have broader implications for guiding adoption trajectories through ongoing evidence synthesis and expanded investigations in under-researched areas to address knowledge gaps. Ultimately, continued monitoring and updated guidance are critical to ensure that ChatGPT’s educational penetration progresses carefully by maximizing benefits and minimizing harms in rapidly evolving AI-powered learning ecosystems. Future Research: Based on the basic mapping provided by this paper, recommended research directions include longitudinal impact studies, research tailored to under-researched contexts such as K-12, qualitative research to capture stakeholder perspectives, development and testing of AI-calibrated assessments as well as explorations that combine conversational and interactive learning technologies, updated systematic reviews, and co-designed implementation research that explain pedagogical strategies that ethically unlock learning potential while mitigating risks in diverse educational environments. Such multilayered tracking can provide critical insights to guide context-specific, responsible ChatGPT integration and monitor impact within rapidly evolving AI-powered education ecosystems.

Aim/Purpose: To explore the effectiveness of utilizing the design thinking approach in developing digital self-directed learning environment to enhance digital literacy skills in Thai higher education. Background: To foster digital literacy skills in higher education, Thai students require more than access to technology. Emphasizing digital self-directed learning and incorporating Design Thinking approach, can empower students to learn and develop their digital skills effectively. This study explores the impact of digital self-directed learning environment, developed using a design thinking approach, on enhancing digital literacy skills among higher education students in Thailand. Methodology: The research methodology involves developing a digital self-directed learning environment, collecting and analyzing data, and using statistical analysis to compare the outcomes between different groups. The sample includes 60 undergraduate students from the School of Industrial Education and Technology at King Mongkut Institute of Technology, divided into a control group (n=30) and an experimental group (n=30). Data analysis involves mean, standard deviation, and one-way MANOVA. Contribution: This research contributes to the evidence supporting the use of Design Thinking in developing digital self-directed learning environment, demonstrating its effectiveness in meeting learners’ needs and improving learning outcomes in higher education. Findings: Key findings include: 1) the digital media and self-directed learning activities plan developed through the design thinking approach received high-quality ratings from experts, with mean scores of 4.87 and 4.93, respectively; and 2) post-lesson comparisons of learning outcome and digital literacy assessment scores revealed that the group utilizing digital media with self-directed learning activities had significantly higher mean scores than the traditional learning group, with a significance level of 0.001. Recommendations for Practitioners: Practitioners in higher education should use design thinking to develop digital self-directed learning environments that enhance digital literacy skills. This approach involves creating high-quality digital media and activities, promoting engagement and improved outcomes. Collaboration and stakeholder involvement are essential for effective implementation. Recommendation for Researchers: Researchers should continue to explore the effectiveness of design thinking approaches in the development of learning environments, as well as their influence on different educational aspects such as student engagement, satisfaction, and overall learning outcomes. Impact on Society: By enhancing digital literacy skills among higher education students, this study contributes to the development of a digitally skilled workforce, encourages lifelong learning, and aids individuals in effectively navigating the challenges of the digital era. Future Research: Future research could explore a broader range of student demographics and educational settings to validate the effectiveness of the Design Thinking approach in enhancing digital literacy. This could include integrating design thinking with alternative digital learning and teaching methods to further improve digital literacy.

Aim/Purpose: The study aims to supplement existing knowledge of information systems by presenting empirical data on the factors influencing the intentions of doctoral students to learn through online platforms. Background: E-learning platforms have become popular among students and professionals over the past decade. However, the intentions of the doctoral students are not yet known. They are an important source of knowledge production in academics by way of teaching and research. Methodology: The researchers collected data from universities in the Delhi National Capital Region (NCR) using a survey method from doctoral students using a convenience sampling method. The model studied was the Technology Readiness and Acceptance Model (TRAM), an integration of the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM). Contribution: TRAM provides empirical evidence that it positively predicts behavioral intentions to learn from online platforms. Hence, the study validated the model among doctoral students from the perspective of a developing nation. Findings: The model variables predicted 49% of the variance in doctoral students’ intent. The TRAM model identified motivating constructs such as optimism and innovativeness as influencing TAM predictors. Finally, doctoral students have positive opinions about the usefulness and ease of use of online learning platforms. Recommendations for Practitioners: Academic leaders motivate scholars to use online platforms, and application developers to incorporate features that facilitate ease of use. Recommendation for Researchers: Researchers can explore the applicability of TRAM in other developing countries and examine the role of cultural and social factors in the intent to adopt online learning. Future Research: The influence of demographic variables on intentions can lead to additional insights.

Aim/Purpose: The study examined how the developed mobile courseware can be used as instructional material to improve senior high school statistics and probability learning, particularly during distance learning caused by the COVID-19 pandemic. The study also aims to assess the gamified mobile courseware’s engagement, functionality, aesthetics, and information quality using the Mobile App Rating Scale (MARS) and a researcher-made Gamified Mobile Courseware Assessment Tool (GMCET). Background: The need to investigate the effectiveness of incorporating game-based elements into mathematics courses through innovative instructional materials inspired the study. The COVID-19 pandemic has made distance learning a necessity, and gamified mobile courseware is a potential solution to improve learning outcomes and engagement in mathematics courses. Methodology: The study employed a descriptive-evaluative method with quantitative and qualitative data to achieve its objectives. Five IT practitioners assessed the developed courseware using the MARS regarding engagement, functionality, aesthetics, and information. A researcher-made GMCET was also used to evaluate the app’s content quality, learning objectives, content presentation, learning assessment, and usability. Five math experts and 12 math teachers rated the app using the GMCET. The study used weighted mean to analyze the quantitative data and content analysis for the qualitative data. Contribution: The study provides insights into the strengths and weaknesses of gamified mobile courseware from the perspective of IT practitioners, math experts, and math teachers. The study’s findings can inform improvements in future iterations of courseware, and the study provides a valuable guide for practitioners looking to develop gamified mobile courseware for mathematics courses. Findings: The quantitative results based on the weighted mean indicate that the IT practitioners had a moderately positive perception of the developed courseware across all categories. At the same time, the math teachers and math experts showed highly positive perceptions of the gamified mobile courseware in Statistics and Probability, rating it highly across all categories. The qualitative data analysis through content analysis highlights the need for improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of the developed app. Recommendations for Practitioners: Practitioners can use the study’s findings to improve the design of gamified mobile courseware for mathematics courses and other content areas. The study recommends that practitioners focus on improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of gamified mobile courseware. Recommendation for Researchers: Future research can build on this study’s findings by exploring the use of gamified mobile courseware in other mathematical courses and other subject areas. Further research can also examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Impact on Society: The study’s findings could improve the effectiveness of gamified mobile courseware in enhancing student learning outcomes in mathematics courses. This can lead to better student performance, improved engagement, and increased interest in mathematics courses, positively impacting society. Future Research: Future research can explore using gamified mobile courseware in other mathematics courses and other subject areas. Additionally, future studies can examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Further research can also investigate the impact of gamified mobile courseware on student motivation, interest, and performance in mathematics courses.

Aim/Purpose: This study examines the use of the Emergency Remote Teaching (ERT) platform by undergraduates of the University of Ibadan, Nigeria, during the COVID-19 pandemic using the constructs of the UTAUT2 model. Five constructs of the UTAUT2 model were adopted to investigate the use of the ERT platform by undergraduates of the university. Background: The Coronavirus (COVID-19) outbreak disrupted academic activities in educational institutions, leading to an unprecedented school closure globally. In response to the pandemic, higher educational institutions adopted different initiatives aimed at ensuring the uninterrupted flow of their teaching and learning activities. However, there is little research on the use of ERT platforms by undergraduates in Nigerian universities. Methodology: The descriptive survey research design was adopted for the study. The multi-stage random sampling technique was used to select 334 undergraduates at the University of Ibadan, Nigeria, while a questionnaire was used to collect data from 271 students. Quantitative data were collected and analyzed using frequency counts, percentages, mean and standard deviation, Pearson Product Moment Correlation, and regression analysis. Contribution: The study contributes to understanding ERT use in the educational institutions of Nigeria – Africa’s most populous country. Furthermore, the study adds to the existing body of knowledge on how the UTAUT2 Model could explain the use of information technologies in different settings. Findings: Findings revealed that there was a positive significant relationship between habit, hedonic motivation, price value, and social influence on the use of ERT platforms by undergraduates. Hedonic motivation strongly predicted the use of ERT platforms by most undergraduates. Recommendations for Practitioners: As a provisional intervention in times of emergencies, the user interface, navigation, customization, and other aesthetic features of ERT platforms should be more appealing and enjoyable to ensure their optimum utilization by students. Recommendation for Researchers: More qualitative research is required on users’ satisfaction, concerns, and support systems for ERT platforms in educational institutions. Future studies could consider the use of ERT by students in different countries and contexts such as students participating in English as a Foreign Language (EFL) and the English for Speakers of other languages (ESOL) programs. Impact on Society: As society faces increased uncertainties of the next global pandemic, this article reiterates the crucial roles of information technology in enriching teaching and learning activities in educational institutions. Future Research: Future research should focus on how different technology theories and models could explain the use of ERT platforms at different educational institutions in other geographical settings and contexts.

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students’ performance and ascertain successful teaching objectives. In pedagogical design, assessment planning is vital in lesson content planning to the extent that curriculum designers and instructors primarily think like assessors. Assessment aids students in redefining their understanding of a subject and serves as the basis for more profound research in that particular subject. Positive results from an evaluation also motivate learners and provide employment directions to the students. Assessment results guide not just the students but also the instructor. Methodology: A modified methodology was used for carrying out the study. The revised methodology is divided into two major parts: the text-processing phase and the classification model phase. The text-processing phase consists of stages including cleaning, tokenization, and stop words removal, while the classification model phase consists of dataset training using a sentiment analyser, a polarity classification model and a prediction validation model. The text-processing phase of the referenced methodology did not utilise tokenization and stop words. In addition, the classification model did not include a sentiment analyser. Contribution: The reviewed literature reveals two major omissions: sentiment responses on using the Moodle for online assessment, particularly in developing countries with unstable internet connectivity, have not been investigated, and variations of the k-fold cross-validation technique in detecting overfitting and developing a reliable classifier have been largely neglected. In this study we built a Sentiment Analyser for Learner Emotion Management using the Moodle for assessment with data collected from a Ghanaian tertiary institution and developed a classification model for future sentiment predictions by evaluating the 10-fold and the 5-fold techniques on prediction accuracy. Findings: After training and testing, the RF algorithm emerged as the best classifier using the 5-fold cross-validation technique with an accuracy of 64.9%. Recommendations for Practitioners: Instead of a closed-ended questionnaire for learner feedback assessment, the open-ended mechanism should be utilised since learners can freely express their emotions devoid of restrictions. Recommendation for Researchers: Feature selection for sentiment analysis does not always improve the overall accuracy for the classification model. The traditional machine learning algorithms should always be compared to either the ensemble or the deep learning algorithms Impact on Society: Understanding learners’ emotions without restriction is important in the educational process. The pedagogical implementation of lessons and assessment should focus on machine learning integration Future Research: To compare ensemble and deep learning algorithms

Aim/Purpose: The study seeks to utilize Augmented Reality (AR) in creating virtual laboratories for engineering education, focusing on enhancing teaching methodologies to facilitate student understanding of intricate and theoretical engineering principles while also assessing engineering students’ acceptance of such laboratories. Background: AR, a part of next-generation technology, has enhanced the perception of reality by overlaying virtual elements in the physical environment. The utilization of AR is prevalent across different disciplines, yet its efficacy in facilitating Science, Technology, Engineering, and Mathematics (STEM) education is limited. Engineering studies, a part of STEM learning, involves complex and abstract concepts like machine simulation, structural analysis, and design optimization; these things would be easy to grasp with the help of AR. This restriction can be attributed to their innovative characteristics and disparities. Therefore, providing a comprehensive analysis of the factors influencing the acceptance of these technologies by students - the primary target demographic – and examining the impact of these factors is essential to maximize the advantages of AR while refining the implementation processes. Methodology: The primary objective of this research is to develop and evaluate a tool that enriches the educational experience within engineering laboratories. Utilizing Unity game engine libraries, digital content is meticulously crafted for this tool and subsequently integrated with geo-location functionalities. The tool’s user-friendly interface allows both faculty and non-faculty members of the academic institution to establish effortlessly the virtual laboratory. Subsequently, an assessment of the tool is conducted through the application of the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, involving the administration of surveys to university students to gauge their level of adaptability. Contribution: The utilization of interactive augmented learning in laboratory settings enables educational establishments to realize notable savings in time and resources, thereby achieving sustainable educational outcomes. The study is of great importance due to its utilization of student behavioral intentions as the underlying framework for developing an AR tool and illustrating the impact of learner experience on various objectives and the acceptance of AR in Engineering studies. Furthermore, the research results enable educational institutions to implement AR-based virtual laboratories to improve student experiences strategically, align with learner objectives, and ultimately boost the adaptability of AR technologies. Findings: Drawing on practice-based research, the authors showcase work samples and a digital project of AR-based Virtual labs to illustrate the evaluation of the adaptability of AR technology. Adaptability is calculated by conducting a survey of 300 undergraduate university students from different engineering departments and applying an adaptability method to determine the behavioral intentions of students. Recommendations for Practitioners: Engineering institutions could leverage research findings in the implementation of AR to enhance the effectiveness of AR technology in practical education settings. Recommendation for Researchers: The authors implement a pragmatic research framework aimed at integrating AR technology into virtual AR-based labs for engineering education. This study delves into a unique perspective within the realm of engineering studies, considering students’ perspectives and discerning their behavioral intentions by drawing upon previous research on technology utilization. The research employs various objectives and learner experiences to assess their influence on students’ acceptance of AR technology. Impact on Society: The use of AR in engineering institutions, especially in laboratory practicals, has a significant impact on society, supported by the UTAUT2 model. UTAUT2 model assesses factors like performance, effort expectancy, social influence, and conditions, showing that AR in education is feasible and adaptable. This adaptability helps students and educators incorporate AR tools effectively for better educational results. AR-based labs allow students to interact with complex engineering concepts in immersive settings, enhancing understanding and knowledge retention. This interactive augmented learning for laboratories saves educational institutions significant time and resources, attaining sustainable learning. Future Research: Further research can employ a more comprehensive acceptance model to examine learners’ adaptability to AR technology and try comparing different adaptability models to determine which is more effective for engineering students.

Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve the technology. Background: Since the release of ChatGPT in 2022, generative artificial intelligence has steadily gained wide use in software development. However, there is conflicting information on the extent to which AI helps developers be more productive in the long term. Also, whether using generated code violates copyright restrictions is a matter of debate. Methodology: ChatGPT and Bing Chat were asked the same question, their responses were recorded, and the percentage of each chatbot’s code that was extraneous was calculated. Also examined were qualitative factors, such as how often the generated code required modifications before it would run. Contribution: This paper adds to the limited body of research on how effective generative AI is at aiding software developers and how to practically address its shortcomings. Findings: Results of AI testing observed that 0.7% of lines and 1.4% of characters in ChatGPT’s responses were extraneous, while 0.7% of lines and 1.1% of characters in Bing Chat’s responses were extraneous. This was well below the 2% threshold, meaning both chatbots can generate concise code. However, code from both chatbots frequently had to be modified before it would work; ChatGPT’s code needed major modifications 30% of the time and minor ones 50% of the time, while Bing Chat’s code needed major modifications 10% of the time and minor ones 70% of the time. Recommendations for Practitioners: Companies building generative AI solutions are encouraged to use this study’s findings to improve their models, specifically by decreasing error rates, adding more training data for programming languages with less public documentation, and implementing a mechanism that checks code for syntactical errors. Developers can use the findings to increase their productivity, learning how to reap generative AI’s full potential while being aware of its limitations. Recommendation for Researchers: Researchers are encouraged to continue where this paper left off, exploring more programming languages and prompting styles than the scope of this study allowed. Impact on Society: As artificial intelligence touches more areas of society than ever, it is crucial to make AI models as accurate and dependable as possible. If practitioners and researchers use the findings of this paper to improve coders’ experience with generative AI, it will make millions of developers more productive, saving their companies money and time. Future Research: The results of this study can be strengthened (or refuted) by a future study with a large, diverse dataset that more fully represents the programming languages and prompting styles developers tend to use. Moreover, further research can examine the reasons generative AI fails to deliver working code, which will yield valuable insights into improving these models.

Aim/Purpose: Despite playing a critical role in shaping the future, 70% of undergraduate engineers report low levels of motivation. Student disengagement and a lack of ownership of their learning are significant challenges in higher education, specifically engineering students in the computer science department. This study investigates the various causes of these problems among first-year undergraduate engineers. Background: Student disengagement has become a significant problem, especially in higher education, leading to reduced academic performance, lower graduation rates, and less satisfaction with learning. The study intends to develop approaches that encourage a more interesting and learner-motivated educational environment. Methodology: This research uses a mixed methods approach by combining quantitative data from a survey-based questionnaire with qualitative insights from focus groups to explore intrinsic and extrinsic motivators, instructional practices, and student perceptions of relevance and application of course content. The aim of this method is to make an all-inclusive exploration into undergraduate engineering students’ perspectives on factors contributing to this disengagement and the need for more ownership. Contribution: Inculcating passion for engineering among learners seems demanding, with numerous educational programs struggling with issues such as a lack of interest by students and no personal investment in learning. Understanding the causes is of paramount importance. The study gives suggestions to help teachers or institutions create a more engaged and ownership-based learning environment for engineering students. Findings: The findings revealed a tangled web influencing monotonous teaching styles, limited opportunities and applications, and a perceived gap between theoretical knowledge and real-world engineering problems. It emphasized the need to implement more active learning strategies that could increase autonomy and a stronger sense of purpose in their learning journey. It also highlights the potential use of technology in promoting student engagement and ownership. Further research is needed to explore optimal implementation strategies for online simulations, interactive learning platforms, and gamification elements in the engineering curriculum. Recommendations for Practitioners: It highlights the complex interplay of intrinsic and extrinsic motivation factors and the need to re-look at instructional practice and emphasize faculty training to develop a more student-centered approach. It also stresses the need to look into the relevance and application of the course content. Recommendation for Researchers: More work needs to be done with a larger, more diverse sample population across multiple institutions and varied sociocultural and economic backgrounds. Impact on Society: Enhancing learners’ educational experience can result in creating a passionate and competent team of engineers who can face future obstacles fearlessly and reduce the production of half-baked graduates unprepared for the profession’s challenges. Future Research: Conduct long-term studies to assess the impact of active learning and technology use on student outcomes and career readiness. Investigate scaling up successful strategies across diverse engineering programs. See if promising practices work well everywhere.

Aim/Purpose: The aim of the study is to test whether the perception of self-regulated learning during text reading in online teacher education is improved by using a digital tool for the use of metacognitive strategies for planning, monitoring, and self-assessment. Background: The use of self-regulated learning is important in reading skills, and for students to develop self-regulated learning, their teachers must master it. Therefore, teaching strategies for self-regulated learning in teacher education is essential. Methodology: The sample size was 252 participants with the tool used by 42% or the participants. A quasi-experimental design was used in a pre-post study. ARATEX-R, a text-based scale, was used to evaluate self-regulated learning. The 5-point Likert scale includes the evaluation of five dimensions: planning strategies, cognition management, motivation management, comprehension assessment and context management. A Generalized Linear Model was used to analyse the results. Contribution: Using the tool to self-regulate learning has led to an improvement during text reading, especially in the dimensions of motivation management, planning management and comprehension assessment, key dimensions for text comprehension and learning. Findings: Participants who use the app perceive greater improvement, especially in the dimensions of motivation management (22,3%), planning management (19.9%) and comprehension assessment (24,6%), which are fundamental dimensions for self-regulation in text reading. Recommendations for Practitioners: This tool should be included in teacher training to enable reflection during the reading of texts, because it helps to improve three key types of strategies in self-regulation: (1) planning through planning management, (2) monitoring through motivation management and comprehension assessment, and (3) self-assessment through comprehension assessment. Recommendation for Researchers: The success of the tool suggests further study for its application in other use cases: other student profiles in higher education, other teaching modalities, and other educational stages. These studies will help to identify adaptations that will extend the tool’s use in education. Impact on Society: The use of Metadig facilitates reflection during the reading of texts in order to improve comprehension and thus self-regulate the learning of content. This reflection is crucial for students’ knowledge construction. Future Research: Future research will focus on enhancing the digital tool by adding features to support the development of cognition and context management. It will also focus on how on adapting the tool to help other types of learners.

Aim/Purpose: This study explores the subject structure, social networks, research trends, and issues in the domain that have the potential to derive an overview of the development of virtual reality-based learning media in vocational education. Background: Notwithstanding the increasingly growing interest in the application of virtual reality in vocational learning, the existing research literature may still leave out some issues necessary for a comprehensive understanding. This study will point out such areas that need more exploration and a more comprehensive synthesis of the literature by conducting a bibliometric analysis. It will be interesting to keep track of the changing concepts and methodologies applied in the development of VR-based learning media in vocational education research. Methodology: This review was carried out using bibliometric methodology, which can highlight patterns of publication and research activity in this hitherto little studied area. The results of the study have the potential to lead to evidence-based priority in VR development, which will tailor work for vocational contexts and set the compass against the growing worldwide interest in this area. The study provides a descriptive analysis of publications, citations, and keyword data for 100 documents published between the years 2013 and 2022 from the Scopus database, which is conducted to illustrate the trends in the field. Contribution: This study also counts as a contribution to understanding the research hotspots of VR-based learning media in vocational education. Through bibliometric analysis, this study thoroughly summarized the relevant research and literature laying a knowledge foundation for researchers and policy makers. Additionally, this analysis identified knowledge gaps, recent trends, and directions for future research. Findings: The bibliometric analysis revealed the following key findings: 1. A growing publication trajectory, with output increasing from 7 articles in 2013 to 25 articles in 2022. 2. The United States led the contributions, followed by China, and Germany. 3. The most prominent authors are affiliated with American medical institutions. 4. Lecture proceedings include familiar sources that reflect this nascent domain. 5. Citation analysis identified highly influential work and researchers. 6. Keyword analysis exposed technology-oriented topics rather than learning-oriented terms. These findings present an emerging landscape with opportunities to address geographic and pedagogical research gaps. Recommendations for Practitioners: This study will be beneficial for designers and developers of VR-based learning programs because it aligns with the most discussed and influential VR technologies within the literature. Such an alignment of an approach with relevant research trends and focus can indeed be very useful for the effective application and use of VR-based learning media for quality improvements in vocational students' learning. Recommendation for Researchers: In fact, in this bibliometric review of VR integration within vocational classrooms, a future call for focused research is presented, especially on teaching methods, course design, and learning impact. This is a framework that seeks to establish its full potential with effective and integrated use of VR in the various vocational curricula and settings of learners. Impact on Society: From the findings of the bibliometric analysis, it is evident that virtual reality technologies (VR) have significantly led to transformation within educational media. There is no denying that the growing interest and investment in the integration of virtual reality into vocational education has been well manifested in the substantive increase in publications in the last decade. This shows what the innovation driving factor is in the United States. At the same time the rapid contributions from China signal worldwide recognition of the potential of VR to improve technical skills training. This study points the way for more research to bridge critical gaps, specifically how VR tools can be used in vocational high school classrooms. Furthermore, research should be aligned to meet specific needs of vocational learners and even promote international cross-border partnerships, pointing out the potential of virtual reality to be a universally beneficial tool in vocational education. The examination of highly cited articles provides evidence of the potential of VR to be an impactful pedagogical tool in vocational education. The findings suggest that researchers need to move forward looking at the trajectory of VR in vocational education and how promising it is in defining the future for innovative and effective learning methodologies. Future Research: This study is an exceptionally valuable contribution, a true landmark in the field of dynamic development, and one that denotes very meaningful implications for the future course of research in the dynamically developing field of bibliometric analysis of VR-based learning media for vocational education. The increase in the number of publications emanates from growing interests in the application of virtual reality (VR) technologies in vocational education. The high concentration of authorship from the USA, along with the ever increasing contributions from China, spotlights the increasing worldwide recognition of the impact of immersive technologies in the enhancement of training in technical skills. These are emerging trends that call for research to exemplify the diverse views and global teamwork opportunities presented by VR technologies. The study also highlights critical areas that need focused attention in future research endeavors. The fact that the embedding of VR tools into classrooms in vocational high schools has been poorly researched points to the major gap in pedagogical research within authentic educational settings. Therefore, further investigations should evaluate teaching methods in VR, lesson designs, and the impacts of VR in specific vocational trades. This supports the need for learner-centered frameworks that are tailor-made to the needs of vocational learners. This calls for more direct and focused investigations into identified research gaps noting a growing dominance in the field of health-related research with the most cited articles in this field, to integrate virtual reality into additional vocational education contexts. In this way, the gaps present an opportunity for researchers to make significant contributions to the development of interventions responsive to the unique needs of vocational learners; this will contribute to strengthening the evidence base for the worldwide implementation of VR within vocational education systems. This was recommended as the intention of such a bibliometric analysis: supporting the potential of VR as a pedagogical tool in vocational contexts and providing grounding for a strong and focused future research agenda within this burgeoning area of educational technology.

Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians’ intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on academicians’ adoption behavior is limited. This study proposes an integrated model incorporating TTF factors and social network characteristics like density, homophily, and connectedness to understand academics’ continuance intentions. Methodology: A qualitative study involving 31 interviews of academics from India examined attitudes and the potential role of social network characteristics like density, homophily, and connectedness in adoption. Results showed positive sentiment towards chatbots and themes on how peer groups accelerate diffusion. In the second phase, a survey of 448 faculty members from prominent Indian universities was conducted to test the proposed research model. Contribution: The study proposes and validates an integrated model of TTF and social network factors that influence academics’ continued usage intentions toward AI chatbots. It highlights the nuanced role of peer networks in shaping adoption. Findings: Task and technology characteristics positively affected academics’ intentions to continue AI chatbot usage. Among network factors, density showed the strongest effect on TTF and perceived usefulness, while homophily and connectedness had partial effects. The study provides insights into designing appropriate AI tools for the academic context. Recommendations for Practitioners: AI chatbot designers should focus on aligning features to academics’ task needs and preferences. Compatibility with academic work culture is critical. Given peer network influences, training and demonstrations to user groups can enhance adoption. Platforms should have capabilities for collaborative use. Targeted messaging customized to disciplines can resonate better with academic subgroups. Multidisciplinary influencers should be engaged. Concerns like plagiarism risks, privacy, and job impacts should be transparently addressed. Recommendation for Researchers: More studies are needed across academic subfields to understand nuanced requirements and barriers. Further studies are recommended to investigate differences across disciplines and demographics, relative effects of specific network factors like size, proximity, and frequency of interaction, the role of academic leadership and institutional policies in enabling chatbot adoption, and how AI training biases impact usefulness perceptions and ethical issues. Impact on Society: Increased productivity in academia through the appropriate and ethical use of AI can enhance quality, access, and equity in education. AI can assist in mundane tasks, freeing academics’ time for higher-order objectives like critical thinking development. Responsible AI design and policies considering socio-cultural aspects will benefit sustainable growth. With careful implementation, it can make positive impacts on student engagement, learning support, and research efficiency. Future Research: Conduct longitudinal studies to examine the long-term impacts of AI chatbot usage in academia. Track usage behaviors over time as familiarity develops. Investigate differences across academic disciplines and roles. Requirements may vary for humanities versus STEM faculty or undergraduate versus graduate students. Assess user trust in AI and how it evolves with repeated usage, and examine trust-building strategies. Develop frameworks to assess pedagogical effectiveness and ethical risks of conversational agents in academic contexts.

This research introduces a hybrid honeypot architecture to bolster security within software-defined networks (SDNs). By combining low-interaction and high-interaction honeypots, the proposed solution effectively identifies and mitigates cyber threats, including port scanning and man-in-the-middle attacks. The architecture is structured into multiple modules that focus on detecting open ports using Vilhala honeypots and simulating targeted and random attack scenarios. This hybrid approach enables comprehensive monitoring and detailed packet-level analysis, providing enhanced protection against advanced online threats. The study also conducts a comparative analysis of different attack detection methods using tools like KFSensor and networking shell commands. The results highlight the hybrid honeypot system's efficacy in filtering malicious traffic and detecting security breaches, making it a robust solution for safeguarding SDNs.

This study focuses on the importance of monitoring student attendance in education and the challenges faced by educators in doing so. Existing methods for attendance tracking have drawbacks, including high costs, long processing times, and inaccuracies, while security and privacy concerns have often been overlooked. To address these issues, the authors present a novel internet of things (IoT)-based self-lecture attendance system (SLAS) that leverages smartphones and QR codes. This system effectively addresses security and privacy concerns while providing streamlined attendance tracking. It offers several advantages such as compact size, affordability, scalability, and flexible features for teachers and students. Empirical research conducted in a live lecture setting demonstrates the efficacy and precision of the SLAS system. The authors believe that their system will be valuable for educational institutions aiming to streamline attendance tracking while ensuring security and privacy.

The purpose of this study is to explore the effect of electronic service quality subdimensions upon the behavioural and praising intentions of users engaged in internet banking. Using the survey method, 203 responses were collected from users of online banking in Turkey. A partial least square structural equation model was constructed to test both the reliability and validity of the measurement, as well as the structural model. The results indicated that emotional benefits, ease of use, and control subdimensions, which are influenced through graphical quality and layout clarity, have a significant and positive impact upon the behavioural and praising intentions of users of online banking. The study did not find support for the direct effect of layout clarity upon behavioural and praising intentions.

The present study attempts to find out the determinants of FinTech adoption for financial inclusion by a microfinance institution in India. The factors such as efficiency, consistency, convenience, reliability are taken as predictors of organisational attitude. Similarly, organisational attitude, ease of use, and perceived benefits are considered as antecedents of organisational adoption intention of FinTech in microfinance institutions of India. The purposive sampling technique was used to get a filled survey instrument by target samples. The results indicate that convenience and consistency in the use of FinTech applications build a favourable attitude to adopt it. Furthermore, perceived benefits are the most important antecedents of the adoption intention of FinTech in the microfinance institution in India. Additionally, the reliability of the application has a positive but insignificant impact on organisational attitude to adopt FinTech. The implications of the present study are discussed.

The present study is a modest attempt to investigate the impact of gender diversity on firm performance of BSE 200 listed companies. The study is based on the secondary data collected from the EMIS database and the corporate governance reports for a period of eight years, i.e., from 2012 to 2019. Sample size of the present study is 174 Indian companies listed in the Bombay Stock Exchange. The study has employed multiple regression models by considering the endogeneity issue to empirically test the impact of gender diversity on firm performance in Indian context. Based on the multiple regression models, we find that the impact of gender diversity is positive and significant on the market-based measure of firm performance. However, the impact becomes negative significant when firm performance was measured by accounting based measure of firm performance.

Smart home devices are vulnerable to various attacks, including distributed-denial-of-service (DDoS) attacks. Current detection techniques face challenges due to nonlinear thought, unusual system traffic, and the fluctuating data flow caused by human activities and device interactions. Identifying the baseline for 'normal' traffic and suspicious activities like DDoS attacks from encrypted data is also challenging due to the encrypted protective layer. This work introduces a concept called synoptic crow search with recurrent transformer network-based DDoS attack detection, which uses the synoptic weighted crow search algorithm to capture varying traffic patterns and prioritise critical information handling. An adaptive recurrent transformer neural network is introduced to effectively regulate DDoS attacks within encrypted data, counting the historical context of the data flow. The proposed model shows effective performance in terms of low false alarm rate, higher detection rate, and accuracy.

Badminton, as a fast and highly technical sport, requires high accuracy in identifying athletes' swing movements. Accurately identifying different swing movements is of great significance for technical analysis, coach guidance, and game evaluation. To improve the recognition accuracy of badminton players' swing movements, this text is based on an improved dense trajectory algorithm to improve the accuracy of recognising badminton players' swing movements. The features are efficiently extracted and encoded. The results on the KTH, UCF Sports, and Hollywood2 datasets demonstrated that the improved algorithm achieved recognition accuracy of 94.2%, 88.2%, and 58.3%, respectively. Compared to traditional methods, the innovation of research lies in optimised feature extraction methods, efficient algorithm design, and accurate action recognition. These results provide new ideas for the research and application of badminton swing motion recognition.

In the competitive landscape of globalised markets, businesses must prioritise cost reduction for sustained competitiveness. This study delves into the dynamic facility layout problem (DFLP) within a cable production company in Kerala, emphasising adaptability to changing production demands. Addressing material handling costs and rearrangement expenses, the research evaluates the efficacy of the current static layout and explores the benefits of transitioning to a dynamic layout. The case study reveals potential cost savings through the strategic restructuring of machine arrangements. The innovative machine learning-based genetic algorithm (ML-GA) integrates machine learning algorithms, genetic algorithms, and a local search method, offering a cutting-edge solution to dynamic facility layout challenges. By considering demand variability and relocation costs, the study provides insights for informed decision-making, emphasising the significance of material flow patterns. This research contributes to enhancing efficiency and profitability, providing practical implications for businesses navigating the complexities of modern manufacturing.

Action recognition plays a vital role in analysing human body behaviour and has significant implications for research and education. However, traditional recognition methods often suffer from issues such as inaccurate time and spatial feature vectors. Therefore, this study addresses the problem of inaccurate recognition of aerobic gymnastics action image data and proposes a visualised three-dimensional convolutional neural network algorithm-based action recognition model. This model incorporates unsupervised visualisation methods into the traditional network and enhances data recognition capabilities through the introduction of a random noise perturbation enhancement algorithm. The research results indicate that the data augmented with noise perturbation achieves the lowest mean square error, reducing the error value from 0.3352 to 0.3095. The use of unsupervised visualisation analysis enables clearer recognition of human actions, and the algorithm model is capable of accurately recognising aerobic movements. Compared to traditional algorithms, the new algorithm exhibits higher recognition accuracy and superior performance.

In the construction sector, moulding machines are crucial in producing concrete products, yet changing their mould can pose challenges for some businesses. This paper presents a case study aimed at reducing the setup time of HESS RH 600 moulding machine. Four alternatives are proposed and evaluated to achieve this goal. The first alternative involves converting internal to external activities, while the subsequent alternatives aim to improve the basic solution. These include building a canopy near the machine (alternative 2), installing an air reservoir (alternative 3), and a comprehensive approach involving building the canopy, installing the air reservoir, and adding a new forklift to facilitate the machine setup process (alternative 4). The analytic hierarchy process (AHP) heuristic method is used to select the best alternative solution based on prespecified criteria. It is found that the application of the single-minute exchange of die (SMED) solution without any further improvement is the most favourable.

This research aims to establish a valid and accurate measurement scale and identify consumer-driven characteristics for minimalism. The study has employed a hybrid approach to produce items for minimalism. Expert interviews were conducted to identify the items for minimalism in the first phase followed by consumer survey to obtain their response in second phase. A five-point Likert scale was used to collect the data. Further, data was subjected to reliability and validity check. Structural equation modelling was used to test the model. The findings demonstrated that there are five dimensions by which consumers perceive minimalism: decluttering, mindful consumption, aesthetic choices, financial freedom, and sustainable lifestyle. The outcome also revealed a high correlation between simplicity and well-being. This study is the first to provide a reliable and valid instrument for minimalism. The results will have several theoretical and practical ramifications for society and policymakers. It will support policymakers in gauging and encouraging minimalistic practices, which enhance environmental performance and lower carbon footprint.