Aim/Purpose: This study seeks to understand the various ways information systems (IS) students experience introductory programming to inform IS educators on effective pedagogical approaches to teaching programming. Background: Many students who choose to major in information systems (IS), enter university with little or no experience of learning programming. Few studies have dealt with students’ learning to program in the business faculty, who do not necessarily have the computer science goal of programming. It has been shown that undergraduate IS students struggle with programming. Methodology: The qualitative approach was used in this study to determine students’ notions of learning to program and to determine their cognitive processes while learning to program in higher education. A cohort of 47 students, who were majoring in Information Systems within the Bachelor of Commerce degree programme were part of the study. Reflective journals were used to allow students to record their experiences and to study in-depth their insights and experiences of learning to program during the course. Using phenomenographic methods, categories of description that uniquely characterises the various ways IS students experience learning to program were determined. Contribution: This paper provides educators with empirical evidence on IS students’ experiences of learning to program, which play a crucial role in informing IS educators on how they can lend support and modify their pedagogical approach to teach programming to students who do not necessarily need to have the computer science goal of programming. This study contributes additional evidence that suggests more categories of description for IS students within a business degree. It provides valuable pedagogical insights for IS educators, thus contributing to the body of knowledge Findings: The findings of this study reveal six ways in which IS students’ experience the phenomenon, learning to program. These ways, referred to categories of description, formed an outcome space. Recommendations for Practitioners: Use the experiences of students identified in this study to determine approach to teaching and tasks or assessments assigned Recommendation for Researchers: Using phenomenographic methods researchers in IS or IT may determine pedagogical content knowledge in teaching specific aspects of IT or IS. Impact on Society: More business students would be able to program and improve their logical thinking and coding skills. Future Research: Implement the recommendations for practice and evaluate the students’ performance.

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: This paper investigates the influence of university student multitasking on their learning success, defined as students’ learning satisfaction and performance. Background: Most research on student multitasking finds student multitasking problematic. However, this research is generally from 2010. Yet, today’s students are known to be digital natives and they have a different, more positive, relationship with mobile technologies. Based on the old findings, most instructors ban mobile technology use during instruction, and design their online courses without regard for the mobile technology use that happens regardless of their ban. This study investigates whether today’s instructors and learning management system interface designers should take into account multitasking with mobile technologies. Methodology: A quasi-experimental design was used in this study. Data were collected from 117 students across two sections of an introductory Management Information Systems class taught by the first author. We took multiple approaches and steps to control for confounding factors and to increase the internal validity of the study. We used a control group as a comparison group, we used a pre-test, we controlled for selection bias, and we tested for demographic differences between groups. Contribution: With this paper, we explicated the relationship between multitasking and learning success. We defined learning success as learning performance and learning satisfaction. Contrary to the literature, we found that multitasking involving IT texting does not decrease students’ learning performance. An explanation of this change is the change in the student population, and the digital nativeness between 2010s and 2020 and beyond. Findings: Our study showed that multitasking involving IT texting does not decrease students’ performance in class compared to not multitasking. Secondly, our study showed that, overall, multitasking reduced the students’ learning satisfaction despite the literature suggesting otherwise. We found that attitude towards multitasking moderated the relationship between multitasking and learning satisfaction as follows. Individuals who had a positive attitude towards multitasking had high learning satisfaction with multitasking. However, individuals who had positive attitude toward multitasking did not necessarily have higher learning performance. Recommendations for Practitioners: We would recommend both instructors and the designers of learning management systems to take mobile multitasking into consideration while designing courses and course interfaces, rather than banning multitasking, and assuming that the students do not do it. Furthermore, we recommend including multitasking into relevant courses such as Management Information Systems courses to make students aware of their own multitasking behavior and their results. Recommendation for Researchers: We recommend that future studies investigate multitasking with different instruction methods, especially studies that make students aware of their multitasking behavior and its outcomes will be useful for next generations. Impact on Society: This paper investigates the role of mobile multitasking on learning performance. Since mobile technologies are ubiquitous and their use in multitasking is common, their use in multitasking affects societal performance. Future Research: Studies that replicate our research with larger and more diverse samples are needed. Future research could explore research-based experiential teaching methods, similar to this study.

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.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 20, 2021

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.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 21, 2022

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: This study seeks to present a learning model of discrete mathematics elements, elucidate the content of teaching, and validate the effectiveness of this learning in a digital education context. Background: Teaching discrete mathematics in the realm of digital education poses challenges, particularly in crafting the optimal model, content, tools, and methods tailored for aspiring computer science teachers. The study draws from both a comprehensive review of relevant literature and the synthesis of the authors’ pedagogical experiences. Methodology: The research utilized a system-activity approach and aligned with the State Educational Standard. It further integrated the theory of continuous education as its psychological and pedagogical foundation. Contribution: A unique model for instructing discrete mathematics elements to future computer science educators has been proposed. This model is underpinned by informative, technological, and personal competencies, intertwined with the mathematical bedrock of computer science. Findings: The study revealed the importance of holistic teaching of discrete mathematics elements for computer science teacher aspirants in line with the Informatics educational programs. An elective course, “Elements of Discrete Mathematics in Computer Science”, comprising three modules, was outlined. Practical examples spotlighting elements of mathematical logic and graph theory of discrete mathematics in programming and computer science were showcased. Recommendations for Practitioners: Future computer science educators should deeply integrate discrete mathematics elements in their teaching methodologies, especially when aligning with professional disciplines of the Informatics educational program. Recommendation for Researchers: Further exploration is recommended on the seamless integration of discrete mathematics elements in diverse computer science curricula, optimizing for varied learning outcomes and student profiles. Impact on Society: Enhancing the quality of teaching discrete mathematics to future computer science teachers can lead to better-educated professionals, driving advancements in the tech industry and contributing to societal progress. Future Research: There is scope to explore the wider applications of the discrete mathematics elements model in varied computer science sub-disciplines, and its adaptability across different educational frameworks.

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: This study aims to explore the value of utilizing non-immersive virtual reality (VR) to create virtual learning environments (VLEs) to support and prepare optometry students in their transition into preclinical and clinical teaching spaces. Background: Digital education is widely integrated into university curricula with the use of online simulators, immersive VR, and other digital technologies to support student learning. This study focuses on non-immersive VR as an accessible and low-friction means of accessing VLEs to reduce students’ learning burden. Methodology: Current optometry students were invited to explore 360° 3D panoramic virtual learning environments of preclinical and clinical teaching spaces. Students were recruited to participate in an online Qualtrics survey and individual semi-structured interviews. Quantitative data was analyzed, and thematic analysis was conducted on qualitative data from students’ responses to identify key takeaways on the accessibility and impact of VLEs on students’ learning. Contribution: Non-immersive VR has utility in alleviating student stress and helping transition students into practicum. The VLEs have the means to supplement the curriculum to provide support to students entering the preclinical and clinical teaching spaces. Findings: Students engaged voluntarily with the novel VLEs and utilized the resources to help familiarize themselves with the preclinical and clinical teaching spaces. The open-access resource supported students in their preparation for practical learning and helped to reduce self-reported stress and build confidence prior to entering practical classes. Many of the students enjoyed the experience of navigating through the spaces, which helped to appease their curiosity and reduce the learning curve associated with entering new spaces. The VLEs did not replace attending practical spaces but rather were supportive learning resources that aided students due to limited face-to-face contact hours. For students with existing familiarity with the spaces, through their in-person attendance in pre-clinical and clinical teaching sessions prior to accessing the VLEs, the digital resources were not as beneficial compared to students who were still transitioning into practicum. Recommendations for Practitioners: Introductory digital resources like non-immersive VR are accessible platforms that help to orient and familiarize students with new environments. VLEs can potentially help to relieve student stress and reduce the learning load associated with entering practicum or new learning spaces. Recommendation for Researchers: More work needs to be done on how student preparation can translate to feeling less stressed and more confident in relation to transitioning from traditional learning environments to practical learning spaces. Impact on Society: A broader application of non-immersive VR can be implemented as an introductory learning preparation tool across different disciplines to alleviate student stress and maximize the limited time in practicum to allow focus on learning outcomes and practical skills. Future Research: Future studies should consider different cohorts to study, with a focus on objective measures of engagement with VLEs. The effect of VLEs on students’ cognitive load should be assessed and assessment of self-perceived stress can be evaluated with instruments such as Cohen’s Perceived Stress Scale.

Aim/Purpose: This paper describes a technologies education model for introducing Simulation Learning and Extended Reality (XR) solution creation skills and knowledge to students at the tertiary education level, which is broadly applicable to higher education-based contexts of teaching and learning. Background: This work is made possible via the model’s focus on advancing knowledge and understanding of a range of digital resources, and the processes and production skills to teach and produce playable educational digital content, including classroom practice and applications. Methodology: Through practice-based learning and technology as an enabler, to inform the development of this model, we proposed a mixed-mode project-based approach of study within a transdisciplinary course for Higher Education students from the first year through to the post-graduate level. Contribution: An argument is also presented for the utility of this model for upskilling Pre-service Teachers’ (PSTs) pedagogical content knowledge in Technologies, which is especially relevant to the Australian curriculum context and will be broadly applicable to various educative and non-Australian settings. Findings: Supported by practice-based research, work samples and digital projects of Simulation Learning and XR developed by the authors are demonstrated to ground the discussion in examples; the discussion that is based around some of the challenges and the technical considerations, and the scope of teaching digital solutions creation is provided. Recommendations for Practitioners: We provide a flexible technologies teaching and learning model for determining content for inclusion in a course designed to provide introductory Simulation Learning and XR solution creation skills and knowledge. Recommendation for Researchers: The goal was to provide key criteria and an outline that can be adapted by academic researchers and learning designers in various higher education-based contexts of teaching and inclusive learning design focused on XR. Impact on Society: We explore how educators work with entities in various settings and contexts with different priorities, and how we recognise expertise beyond the institutional interests, beyond discipline, and explore ‘what is possible’ through digital technologies for social good and inclusivity. Future Research: The next step for this research is to investigate and explore how XR and Simulation Learning could be utilised to accelerate student learning in STEM and HASS disciplines, to promote knowledge retention and a higher level of technology-enhanced learning engagement.

Aim/Purpose: The emergence of massive open online courses (MOOCs) has fostered the creation of co-located learning communities; however, there is limited research on the types of interactions unfolding in these spaces. Background: This study explores Peer 2 Peer University’s Learning Circles, a project that allows individuals to take MOOCs together at the library. I investigated the patterns that emerged from the interactions between facilitators, learners, course materials, and digital media in the pilot round of these Learning Circles. Methodology: This study employs an ethnography of hybrid spaces (online/offline participant observations, in-depth interviews, and artifact collection) of face-to-face study groups taking place at library branches in a Midwest metropolitan area. Data analysis employs the constant comparison method. Contribution: Interactions taking place in the Learning Circles increased individuals’ agency as learners and subverted the MOOC model through processes of technological appropriation. Findings: The findings reveal that interactions within Learning Circles created a dynamic negotiation of roles, produced tension points, enabled a distributed model of knowledge, and structured study routines. The pilot round of Learning Circles attracted diverse participants beyond the typical digitally literate MOOC student. Many of them had no previous experience taking online courses and, in some cases, no Internet connection at home. This paper argues that Learning Circles favored the appropriation of artifacts (technologies) and increased participants’ agency as learners in the Internet age. Recommendations for Practitioners: Practitioners can use the Learning Circles model to benefit disenfranchised individuals by providing them with access to materials resources and a network of peers that can help increase their agency as learners. Recommendation for Researchers: This study suggests that it is fundamental to pay attention to learning initiatives that are unfolding outside the scope of traditional and formal education. Impact on Society: Open educational resources and public libraries are opening new pathways for learning beyond traditional higher education institutions. Future Research: Future research can explore how the learning circles are adapted in cultural contexts outside the United States.

Aim/Purpose: This research explores the influence of organizational-level and individual-level creativity and innovation and the technology acceptance model toward the higher education creative environment that consists of research creativity and teaching creativity. Background: Creativity and innovation are essential pillars for higher education institutions (HEIs). The two terms are interconnected, where creativity is referring to finding better ideas to do the work, while innovation is referring to how to do and implement these creative ideas. Choosing the optimal creative process and the organizational support needed to develop it is an important goal in achieving a creative and inventive environment. For the success of the creative environment to ensure the improvement of higher education institutions, information technology as social networking sites plays a crucial part in the creative process within universities. However, assessing the creativity and innovation of Saudi higher education institutions has not been well recognized. Universities today serve as knowledge-based institutions because they are at the forefront of cutting-edge R&D and scientific innovations. Creating such a productive research environment in universities, however, necessitates a work culture that encourages employees to be more creative while also encouraging the creation of new ideas and innovations. Methodology: A survey instrument was utilized as a quantitative method for this research to gather data from the study sample on the influencing variables employed in the research framework. Respondent data were analyzed using a disjoint two-stage method using PLS-SEM path modelling. Contribution: The results of this research contribute to the theoretical and scientific literature by offering a model of creativity and innovation in higher education institutions. The model proposes an optimal blend of organizational, individual, and technology variables that contribute to the development of the Higher Education Creative Environment in HEIs via creativity in teaching and research and a culture of innovation. In another way, the proposed framework especially helps to comprehend the challenges regulating establishing teaching and research creativity in HEIs via the adoption of organizational, individual, and technology enablers identified as part of this study. Findings: According to the results, organizational factors such as organizational encouragement, freedom, and challenging work have a positive relationship with the higher education creative environment. However, realistic work pressure, a lack of organizational impediments, managerial encouragement, and work group support is insufficient to affect the creative environment in higher education in Saudi Arabia. Individual variables (creative thinking skills and expertise, for example) also have a positive impact on the higher education creative environment. In the higher education creative environment, however, the influence of intrinsic motivation is insignificant. Finally, technology factors such as social networking site adoption intention, perceived usefulness, and perceived ease of use have the potential to influence the higher education creative environment. Recommendations for Practitioners: On the practical front, the obvious recommendation of this research is that it enables top leadership in Saudi HEIs to rethink the norms of creativity and innovation in their institutions, thereby instilling a mindset guided by a flourishing culture of creativity in the HEI environment with a specific focus on creativity practices in research and teaching domains. Furthermore, to promote the environment’s creativity within Saudi Arabian HEIs, university leaders must consider the suggested Organizational, Individual, and Technology factors as key enablers of creativity and innovation, which will guide them in revisiting their strategic actions in terms of further augmenting the creative performance of their academic’s staff, thereby sustaining a culture of Higher Education Creative Environment (HECE). Recommendation for Researchers: This study addressed many organizational, individual, and technology variables that facilitate Saudi Arabian HECE accomplishment in the form of research and teaching creativity. Furthermore, fresh insights for Saudi public HEIs are revealed when the success aspects of the creative environment are considered. If academic leadership at Saudi HEIs is to encourage the creative environment in general and creativity in teaching and research, it would be suitable for them to highlight individual, organizational, and technology success elements. As a result, their HEIs will be able to produce more innovative research, products, and services that can support and meaningfully achieve national transformation initiatives, opening the path for a transition into a knowledge-based economy. Impact on Society: In fact, this research is based on a quantitative research method, and the findings were also significant especially considering the current global crises. It is clearly understood by this process that includes organizational, individual, and technology factors as key enablers of the creative performance of academic staff, thereby sustaining a culture of HECE. Future Research: While providing the research model, it is probable that this study overlooked any other crucial aspects influencing creativity and innovation. As a result, future research should look at additional variables that may impact HECE in Saudi Arabian HEIs. Furthermore, while this study focused on deriving HECE with a particular emphasis on research and teaching creativity as results, future research might look at deriving other creativity outcomes (e.g., entrepreneurial creativity) within the investigated HECE dimension.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 22, 2023

Aim/Purpose: This article explores the critical need for adaptable educational models in times of crisis, focusing on strategies to overcome infrastructural and digital inequalities exacerbated by the COVID-19 pandemic. Background: By examining a case study of an offline digital library project implemented in South Sudan, this paper seeks to examine the impact of an offline digital educational solution for low-resource and crisis situations. Methodology: The authors utilize a mixed-methods approach, integrating both qualitative interviews and quantitative data analysis, to evaluate the use and impact of the SolarSPELL Initiative’s offline digital libraries in South Sudan. Contribution: This study contributes to our understanding of digital and information literacy within crisis contexts, highlighting the vital role of localized, offline content. Findings: The findings demonstrate that offline digital solutions can effectively mitigate educational disruptions by providing an accessible means to continue education during emergencies. Recommendations for Practitioners: Recommendations for practitioners include the adoption of robust offline digital learning solutions to promote educational continuity. Recommendation for Researchers: The authors recommend that researchers continue investigating the potential of offline digital educational solutions for low-resource and crisis situations. Impact on Society: Ultimately, this article finds that offline digital libraries, when paired with skill-building, are a viable means to lessen digital disparities and promote educational continuity in times of crisis and beyond. Future Research: The study suggests further exploration into the long-term impacts of such interventions on learning outcomes.

Aim/Purpose: This paper explores the potential value of critical thinking in computer science education and discusses strategies for its integration across the curriculum. Background: As technology rapidly evolves and becomes increasingly integrated into society, there is a growing need for computer science graduates who can think critically about the ethical, societal, and technical implications of their work. Methodology: This study employs a conceptual analysis approach, reviewing existing literature on critical thinking in computer science education and synthesising insights from various sources. The analysis focuses on identifying challenges in implementing critical thinking instruction and proposing practical solutions. Contribution: This paper provides an overview of the current discourse on integrating critical thinking into computer science curricula. It explores the distinction between critical thinking and computational thinking, discusses various pedagogical approaches, and offers insights into potential challenges of implementation. Findings: The paper identifies six key challenges in embedding critical thinking into computer science education. It proposes initial steps to address these challenges, including curriculum redesign, innovative assessment methods, and faculty development strategies. Recommendations for Practitioners: Educators should adopt a balanced approach that complements technical education with critical thinking exercises, using diverse teaching methods such as dialogue-based teaching and authentic instruction. Recommendation for Researchers: Future research should focus on empirical studies to assess the effectiveness of the proposed solutions and develop standardised tools for evaluating critical thinking skills in computer science. Impact on Society: By enhancing critical thinking skills in computer science education, we can produce graduates who are better equipped to address complex technological challenges and their societal implications. Future Research: Further investigation is needed into the most effective pedagogical approaches for teaching critical thinking in computer science, with a focus on multidisciplinary perspectives.

Aim/Purpose: The teaching of appropriate problem-solving techniques to novice learners in undergraduate software development education is often poorly defined when compared to the delivery of programming techniques. Given the global need for qualified designers of information technology, the purpose of this research is to produce a foundational template for an educational software development methodology grounded in the established literature. This template can be used by third-level educators and researchers to develop robust educational methodologies to cultivate structured problem solving and software development habits in their students while systematically teaching the intricacies of software creation. Background: While software development methodologies are a standard approach to structured and traceable problem solving in commercial software development, educational methodologies for inexperienced learners remain a neglected area of research due to their assumption of prior programming knowledge. This research aims to address this deficit by conducting an integrative review to produce a template for such a methodology. Methodology: An integrative review was conducted on the key components of Teaching Software Development Education, Problem Solving, Threshold Concepts, and Computational Thinking. Systematic reviews were conducted on Computational Thinking and Software Development Education by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) process. Narrative reviews were conducted on Problem Solving and Threshold Concepts. Contribution: This research provides a comprehensive analysis of problem solving, software development education, computational thinking, and threshold concepts in computing in the context of undergraduate software development education. It also synthesizes review findings from these four areas and combines them to form a research-based foundational template methodology for use by educators and researchers interested in software development undergraduate education. Findings: This review identifies seven skills and four concepts required by novice learners. The skills include the ability to perform abstraction, data representation, decomposition, evaluation, mental modeling, pattern recognition, and writing algorithms. The concepts include state and sequential flow, non-sequential flow control, modularity, and object interaction. The teaching of these skills and concepts is combined into a spiral learning framework and is joined by four development stages to guide software problem solving: understanding the problem, breaking into tasks, designing, coding, testing, and integrating, and final evaluation and reflection. This produces the principal finding, which is a research-based foundational template for educational software development methodologies. Recommendations for Practitioners: Focusing introductory undergraduate computing courses on a programming syllabus without giving adequate support to problem solving may hinder students in their attainment of development skills. Therefore, providing a structured methodology is necessary as it equips students with essential problem-solving skills and ensures they develop good development practices from the start, which is crucial to ensuring undergraduate success in their studies and beyond. Recommendation for Researchers: The creation of educational software development methodologies with tool support is an under-researched area in undergraduate education. The template produced by this research can serve as a foundational conceptual model for researchers to create concrete tools to better support computing undergraduates. Impact on Society: Improving the educational value and experience of software development undergraduates is crucial for society once they graduate. They drive innovation and economic growth by creating new technologies, improving efficiency in various industries, and solving complex problems. Future Research: Future research should concentrate on using the template produced by this research to create a concrete educational methodology adapted to suit a specific programming paradigm, with an associated learning tool that can be used with first-year computing undergraduates.

Aim/Purpose: This study presents some activities that integrate computational thinking (CT) into mathematics lessons utilizing GeoGebra to promote constructionist learning. Background: CT activities in the Indonesian curriculum are dominated by worked examples with less plugged-mode activities that might hinder students from acquiring CT skills. Therefore, we developed mathematics and CT (math+CT) lessons to promote students’ constructionist key behaviors while learning. Methodology: The researchers utilized an educational design research (EDR) to guide the lesson’s development. The lesson featured 11 applets and 22 short questions developed in GeoGebra. To improve the lesson, it was sent to eight mathematics teachers and an expert in educational technology for feedback, and the lesson was improved accordingly. The improved lessons were then piloted with 17 students, during which the collaborating mathematics teachers taught the lessons. Data were collected through the students’ work on GeoGebra, screen recording when they approached the activities, and interviews. We used content analysis to analyze the qualitative data and presented descriptive statistics to quantitative data. Contribution: This study provided an example and insight into how CT can be enhanced in mathematics lessons in a constructionist manner. Findings: Students were active in learning mathematics and CT, especially when they were engaged in programming and debugging tasks. Recommendations for Practitioners: Educators are recommended to use familiar mathematics software such as GeoGebra to support students’ CT skills while learning mathematics. Additionally, our applets are better run on big-screen devices to optimize students’ CT programming and debugging skills. Moreover, it is recommended that students work collaboratively to benefit from peer feedback and discussion. Recommendation for Researchers: Collaboration with teachers will help researchers better understand the situation in the classroom and how the students will respond to the activities. Additionally, it is important to provide more time for students to get familiar with GeoGebra and start with fewer errors to debug. Future Research: Further research can explore more mathematics topics when integrating CT utilizing GeoGebra or other mathematics software or implement the lessons with a larger classroom size to provide a more generalizable result and deeper understanding.

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 review’s main objective was to examine the existing literature on the use of 3D printers in primary education, covering students aged six to twelve across general, special, and inclusive educational environments. Background: A review of the literature indicated a significant oversight – prior reviews insufficiently distinguish the application of 3D printing in primary education from its utilization at higher educational tiers or focused on particular subject areas and learning domains. Considering the distinct nature and critical role of primary education in developing young students’ cognitive abilities and skills, it is essential to concentrate on this specific educational stage. Methodology: The scoping review was selected as the preferred research method. The methodological robustness was augmented through the utilization of the backward snowballing technique. Consequently, a total of 50 papers were identified and subjected to thorough analysis. Contribution: This review has methodically compiled and analyzed the literature on 3D printing use among elementary students, offering a substantial addition to academic conversations. It consolidated and organized research on 3D printers’ educational uses, applying robust and credible criteria. Findings: Many studies featured small sample sizes and limited research on inclusive and special education. The analysis revealed 82 distinct research goals and 13 educational fields, with STEM being the predominant focus. Scholars showed considerable interest in how 3D printers influence skills like creativity and problem-solving, as well as emotions such as engagement and motivation. The majority of studies indicated positive outcomes, enhancing academic achievement, engagement, collaboration, creativity, interest, and motivation. Nonetheless, challenges were noted, highlighting the necessity for teacher training, the expense of equipment, technical difficulties, and the complexities of blending new methods with traditional curricula. Recommendations for Practitioners: To capitalize on the benefits that 3D printers bring, curriculum planners are urged to weave them into their programs, ensuring alignment with educational standards and skill development. The critical role educators play in the effective implementation of this technology necessitates targeted professional development programs to equip them with the expertise for successful integration. Moreover, 3D printing presents a unique opportunity to advance inclusive education for students with disabilities, offering tailored learning experiences and aiding in creating assistive technologies. In recognizing the disparities in access to 3D printing, educational leaders must address the financial and logistical barriers highlighted in the literature. Strategic initiatives are essential to democratize 3D printing access, ensuring all students benefit from this educational tool. Recommendation for Researchers: Comparative studies are critical to elucidate the specific advantages and limitations of 3D printing technology due to the scarcity of research contrasting it with other tools. The variability in reporting durations of interventions and research environments underscores the necessity for uniform methodologies and benchmarks. Because research has predominantly focused on STEM/STEAM education, expanding into different educational areas could provide a comprehensive understanding of 3D printing’s capabilities. The existence of neutral and negative findings signals an opportunity for further investigation. Exploring the factors that impede the successful integration of 3D printing will inform the creation of superior pedagogical approaches and technological refinements. Future Research: As the review confirmed the significant promise of 3D printing technology in enriching education, especially in the context of primary education, the imperative for continued research to refine its application in primary education settings is highlighted.

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: To conduct a needs assessment and subsequently create micro-storytelling media aimed at enhancing the Digital Intelligence Quotient (DQ) skills of young individuals. Background: In today's digital society, DQ has emerged as a vital skill that elevates individuals in all aspects of life, from daily living to education. To empower Thai youth, this study seeks to innovate DQ content by adapting it into a digital format known as micro-storytelling. This unique approach combines the art of storytelling with digital elements, creating engaging and effective micro-learning media Methodology: The methodology comprises three phases: 1) assessing the need for digital micro-storytelling development; 2) developing digital micro-storytelling; and 3) evaluating the DQ skills among young individuals. The sample group consisted of 55 higher education learners for needs assessment and 30 learners in the experiment group. Data analysis involves PNI modified, mean, and standard deviation. Contribution: This research contributes by addressing the urgent need for DQ skills in the digital era and by providing a practical solution in the form of digital micro-storytelling, tailored to the preferences and needs of Thai youth. It serves as a valuable resource for educators and policymakers seeking to empower young learners with essential digital competencies. Findings: The findings demonstrate three significant outcomes: 1) The learners wanted to organize their own learning experience with self-paced learning in a digital landscape, and they preferred digital media in the form of video. They were most interested in developing DQ to enhance their understanding of digital safety, digital security, and digital literacy; 2) according to a consensus of experts, digital micro-storytelling has the greatest degree of quality in terms of its development, content, and utilization, with an overall average of 4.86; and 3) the overall findings of the assessment of DQ skills indicate a favorable level of proficiency. Recommendations for Practitioners: Align materials with micro-learning principles, keeping content concise for effective knowledge retention. Empower students to personalize their digital learning and promote self-paced exploration based on their interests. Recommendation for Researchers: Researchers should continuously assess and update digital learning materials to align with the evolving digital landscape and the changing needs of students and investigate the long-term effects of DQ improvement, especially in terms of online safety and digital literacy in students' future lives and careers. Impact on Society: This study's impact on society is centered around fostering a DQ, promoting innovative educational approaches, and elevating Thai youth with essential digital skills. It contributes to a safer, more informed, and digitally literate generation prepared for the challenges of the digital era. Future Research: Undertake comparative studies to analyze the effectiveness of different digital learning formats and methodologies. Comparing micro-storytelling with other approaches can help identify the most efficient and engaging methods for enhancing DQ.

Aim/Purpose: The digital ecosystem has contributed to the acceleration of digital and mobile educational tools across institutions worldwide. The research displays educators’ perspectives on web applications on mobile devices that can be used to engage and challenge students while impacting their learning. Background: Explored are elements of technology in education and challenges and successes reported by instructors to shift learning from static to dynamic. Methodology: Insights for this study were gained through questionnaires and focus groups with university educators in the United Arab Emirates. Key questions addressed are (1) challenges/benefits, (2) types of mobile technology applications used by educators, and (3) strategies educators use to support student learning through apps. The research is assisted by focus groups and a sample of 42 completed questionnaires. Contribution: The work contributes to web/mobile strategic considerations in the classroom that can support student learning and outcomes. Findings: The results reported showcase apps that were successfully implemented in classrooms and provide a perspective for today’s learning environment that could be useful for instructors, course developers, or any educational institutions. Recommendations for Practitioners: Academics can integrate suggested tools and explore engagement and positive associations with tools and technologies. Recommendation for Researchers: Researchers can consider new learning applications, mobile devices, course design, learning strategies, and student engagement practices for future studies. Impact on Society: Digitization and global trends are changing how educators teach, and students learn; therefore, gaps need to be continually filled to keep up with the pace of ever-evolving digital technologies that can engage student learning. Future Research: Future research may focus on interactive approaches toward mobile devices in higher education learning and shorter learning activities to engage students.

Aim/Purpose: This exploratory qualitative case study examines the perceptions of high-school learners of English regarding a pedagogical intervention involving progressive reduction of captions (full, sentence-level, keyword captions, and no-captions) in enhancing language learning. Background: Recognizing the limitations of caption usage in fostering independent listening comprehension in non-captioned environments, this research builds upon and extends the foundational work of Vanderplank (2016), who highlighted the necessity of a comprehensive blend of tasks, strategies, focused viewing, and the need to actively engage language learners in watching captioned materials. Methodology: Using a qualitative research design, the participants were exposed to authentic video texts in a five-week listening course. Participants completed an entry survey, and upon interaction with each captioning type, they wrote individual reflections and participated in focus group sessions. This methodological approach allowed for an in-depth exploration of learners’ experiences across different captioning scenarios, providing a nuanced understanding of the pedagogical intervention’s impact on their perceived language development process. Contribution: By bridging the research-practice gap, our study offers valuable insights into designing pedagogical interventions that reduce caption dependence, thereby preparing language learners for success in real-world, caption-free listening scenarios. Findings: Our findings show that learners not only appreciate the varied captioning approaches for their role in supporting text comprehension, vocabulary acquisition, pronunciation, and on-task focus but also for facilitating the integration of new linguistic knowledge with existing background knowledge. Crucially, our study uncovers a positive reception towards the gradual shift from fully captioned to uncaptioned materials, highlighting a stepwise reduction of caption dependence as instrumental in boosting learners’ confidence and sense of achievement in mastering L2 listening skills. Recommendations for Practitioners: The implications of our findings are threefold: addressing input selection, task design orchestration, and reflective practices. We advocate for a deliberate selection of input that resonates with learners’ interests and contextual realities alongside task designs that progressively reduce caption reliance and encourage active learner engagement and collaborative learning opportunities. Furthermore, our study underscores the importance of reflective practices in enabling learners to articulate their learning preferences and strategies, thereby fostering a more personalized and effective language learning experience. Recommendation for Researchers: Listening comprehension is a complex process that can be clearly influenced by the input, the task, and/or the learner characteristics. Comparative studies may struggle to control and account for all these variables, making it challenging to attribute observed differences solely to caption reduction. Impact on Society: This research responds to the call for innovative teaching practices in language education. It sets the stage for future inquiries into the nuanced dynamics of caption usage in language learning, advocating for a more learner-centered and adaptive approach. Future Research: Longitudinal quantitative studies that measure comprehension as captions support is gradually reduced (full, partial, and keyword) are strongly needed. Other studies could examine a range of individual differences (working memory capacity, age, levels of engagement, and language background) when reducing caption support. Future research could also examine captions with students with learning difficulties and/or disabilities.

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.

Table of Contents of the Journal of Information Technology Education: Innovations in Practice, Volume 23, 2024

Forensic document forgery investigations have elevated the need for source identification for printed documents during the past few years. It is necessary to create a reliable and acceptable safety testing instrument to determine the credibility of printed materials. The proposed system in this study uses a neural network to detect the original printer used in forensic document forgery investigations. The study uses a deep neural network method, which relies on the quality, texture, and accuracy of images printed by various models of Canon and HP printers. The datasets were trained and tested to predict the accuracy using logical function, with the goal of creating a reliable and acceptable safety testing instrument for determining the credibility of printed materials. The technique classified the model with 95.1% accuracy. The proposed method for identifying the source of the printer is a non-destructive technique.

Currently, Android is a booming technology that has occupied the major parts of the market share. However, as Android is an open-source operating system there are possibilities of attacks on the users, there are various types of attacks but one of the most common attacks found was malware. Malware with machine learning (ML) techniques has proven as an impressive result and a useful method for malware detection. Here in this paper, we have focused on the analysis of malware attacks by collecting the dataset for the various types of malware and we trained the model with multiple ML and deep learning (DL) algorithms. We have gathered all the previous knowledge related to malware with its limitations. The machine learning algorithms were having various accuracy levels and the maximum accuracy observed is 99.68%. It also shows which type of algorithm is preferred depending on the dataset. The knowledge from this paper may also guide and act as a reference for future research related to malware detection. We intend to make use of Static Android Activity to analyse malware to mitigate security risks.

In today's world, malware has become a part and threat to our computer systems. All electronic devices are very susceptible/vulnerable to various threats like different types of malware. There is one subset of malware called ransomware, which is majorly used to have large financial gains. The attacker asks for a ransom amount to regain access to the system/data. When dynamic technique using machine learning is used, it is very important to select the correct set of features for the detection of a ransomware attack. In this paper, we present two novel algorithms for the detection of ransomware attacks. The first algorithm is used to assign the time stamp to the features (API calls) for the ordering and second is used for the ordering and ranking of the features for the early detection of a ransomware attack.

Scientific progress has a significant impact on both reality and the law that applies to it. As the ICT system has positive points that are considered an added value to it, it made it easier for people to perform their tasks and facilitate interpersonal communication for individuals, saved effort and money, and reduced the time needed to accomplish part of the duties. However, at the same time, it has become a means of committing offences and a fertile space for the existence of offence, to the extent that offence in our current era has become the result of intermarriage between human intelligence and artificial intelligence. Thus, the issue of proving cybercrimes requires a deep exploration in the notion of the authenticity of audio evidence obtained from electronic searches, as well as the process of eavesdropping and recording phone calls, and the use of expert and inspection procedures in criminal lawsuits and its impact on proof before the criminal courts.

The use of electronic means of a public official in carrying out their duties may lead to an instance wherein the person discloses confidential information, which can significantly impact their obligations. After verifying this act as part of electronic misconduct, disciplinary action is enforced upon the concerned party to rectify and ensure proper functioning in delivering public services without any disturbance or infringement. The study presents several significant findings regarding the absence of comparative regulations concerning electronic violations and their judicial evidence. It provides recommendations such as modifying legislative frameworks to enhance public utility disciplinary systems and incorporating rules for electric violations. The fundamental focus revolves around assessing, verifying, and punishing digital misconduct by management or regulatory bodies. Additionally, this research employs descriptive-analytical methods comparing the Jordanian Law with its Egyptian counterpart in exploring these issues.

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.