A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

The ways people connect, interact, share, and communicate have changed due to recent developments in information technology. These developments, categorized as social media, have captured the attention of business executives, technologists, and education professionals alike, and have altered many business models. Additionally, the concept of social media impacts numerous sub-disciplines within business and has become an important issue with operational, tactical, and strategic considerations. Despite this interest, many business schools do not have courses involving social media technologies and applications. In those that do, the placement and focus of the course varies considerably. This article provides motivation and insight into the process of developing an approach for effectively teaching social media use in business. Additionally, it offers implementation examples of courses taught at three major universities. The article concludes with lessons-learned that will give instructors practical guidance and ensure that social media courses taught in a business school provide students with a solid basis for integrating social media into business practice.

Since the advent of the iPhone and rise of mobile technologies, educational apps represent one of the fastest growing markets, and both the mobile technology and educational app markets are predicted to continue experiencing growth into the foreseeable future. The irony, however, is that even with a booming market for educational apps, very little research regarding the quality of them has been conducted. Though some instruments have been developed to evaluate apps geared towards student learning, no such instrument has been created for teacher resource apps, which are designed to assist teachers in completing common tasks (e.g., taking attendance, communicating with parents, monitoring student learning and behavior, etc.). Moreover, when teachers visit the App Store or Google Play to learn about apps, the only ratings provided to them are generic, five-point evaluations, which do not provide qualifiers that explain why an app earned three, two, or five points. To address that gap, previously conducted research related to designing instructional technologies coupled with best practices for supporting teachers were first identified. That information was then used to construct a comprehensive rubric for assessing teacher re-source apps. In this article, a discussion that explains the need for such a rubric is offered before describing the process used to create it. The article then presents the rubric and discusses its different components and potential limitations and concludes with suggestions for future research based on the rubric.

The pilot research presented here explores the classroom use of Emerging Literacy in Mathematics (ELM) software, a research-based bilingual interactive multimedia instructional tool, and its potential to develop emerging numeracy skills. At the time of the study, a central theme of early mathematics curricula, Number Concept, was fully developed. It was broken down into five mathematical concepts including counting, comparing, adding, subtracting and decomposing. Each of these was further subdivided yielding 22 online activities, each building in a level of complexity and abstraction. In total, 234 grade one students from 12 classes participated in the two-group post-test study that lasted about seven weeks and for which students in the experimental group used ELM for about 30 minutes weekly. The results for the final sample of 186 students showed that ELM students scored higher on the standardized math test (Canadian Achievement Test, 2008) and reported less boredom and lower anxiety as measured on the Academic Emotions Questionnaire than their peers in the control group. This short duration pilot study of one ELM theme holds great promise for ELM’s continued development.

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question: When compared to the online and traditional instructional approaches, does the flipped instructional approach have a greater impact on student academic performance with specific course requirements in a C# programming course? Methodology: Quantitative research design conducted over eight 16-week semesters among a total of 271 participants who were undergraduate students en-rolled in a C# programming course. Data collected were grades earned from specific course requirements and were analyzed with the nonparametric Kruskal Wallis H-Test using IBM SPSS Statistics, Version 23. Contribution: Provides empirical findings related to the impact that different instructional approaches have on student academic performance in a C# programming course. Also describes implications and recommendations for instructors of programming courses regarding instructional approaches that facilitate active learning, student engagement, and self-regulation. Findings: Resulted in four statistically significant findings, indicating that the online and flipped instructional approaches had a greater impact on student academic performance than the traditional approach. Recommendations for Practitioners: Implement instructional approaches such as online, flipped, or blended which foster active learning, student engagement, and self-regulation to increase student academic performance. Recommendation for Researchers: Build upon this study and others similar to it to include factors such as gender, age, ethnicity, and previous academic history. Impact on Society: Acknowledge the growing influence of technology on society as a whole. Higher education coursework and programs are evolving to encompass more digitally-based learning contexts, thus compelling faculty to utilize instructional approaches beyond the traditional, lecture-based approach. Future Research: Increase the number of participants in the flipped instructional approach to see if it has a greater impact on student academic performance. Include factors beyond student academic performance to include gender, age, ethnicity, and previous academic history.

Aim/Purpose: This paper presents the findings of an Activity-Oriented Teaching Strategy (AOTS) conducted for a postgraduate level Software Engineering (SE) course with the aim of imparting meaningful software development experience for the students. The research question is framed as whether the activity-oriented teaching strategy helps students to acquire practical knowledge of Software Engineering and thus bridge the gap between academia and software industry. Background: Software Engineering Education (SEE) in India is mainly focused on teaching theoretical concepts rather than emphasizing on practical knowledge in software development process. It has been noticed that many students of CS/IT background are struggling when they start their career in the software industry due to inadequate familiarity with the software development process. In the current context of SE education, there is a knowledge gap between the theory learned in the classroom and the actual requirement demanded by the software industry. Methodology: The methodology opted for in this study was action research since the teachers are trying to solve the practical problems and deficiencies encountered while teaching SE. There are four pedagogies in AOTS for fulfilling the requirements of the desired teaching strategy. They are flipped classroom, project role-play for developing project artifacts, teaching by example, and student seminars. The study was conducted among a set of Postgraduate students of the Software Engineering programme at Cochin University of Science and Technology, India. Contribution: AOTS can fulfil both academic and industrial requirements by actively engaging the students in the learning process and thus helping them develop their professional skills. Findings: AOTS can be molded as a promising teaching strategy for learning Software Engineering. It focuses on the essential skill sets demanded by the software industry such as communication, problem-solving, teamwork, and understanding of the software development processes. Impact on Society: Activity-oriented teaching strategies can fulfil both academic and industrial requirements by actively engaging the students in the SE learning process and thus helping them in developing their professional skills. Future Research: AOTS can be refined by adding/modifying pedagogies and including different features like an online evaluation system, virtual classroom etc.

Aim/Purpose: This study was aimed at enhancing students’ learning of software engineering methods. A collaboration between the Computer Science, Business Management, and Product Design programs was formed to work on actual projects with real clients. This interdisciplinary form of collaboration simulates the realities of a diverse Software Engineering team. Background: A collaborative approach implemented through projects has been the established pedagogy for introducing the Software Engineering course to undergraduate Computer Science students. The collaboration, however, is limited to collaboration among Computer Science students and their clients. This case study explored an enhancement to the collaborative approach to project development by integrating other related disciplines into the project development framework; hence, the Interdisciplinary Approach. Methodology: This study adopted the case method approach. An interdisciplinary service innovation activity was proposed to invite other disciplines in the learning process of the computer science students. The agile methodology Scrum was used as the software development approach during project development. Survey data were collected from the students to establish (a) their perception of the interdisciplinary approach to project development; (b) the factors that influenced success or failure of their team to deliver the project; and (c) the perceived skills or knowledge that they acquired from the interdisciplinary approach. Analysis of data followed a mixed method approach. Contribution: The study improved the current pedagogy for Software Engineering education by integrating other related disciplines into the software project development framework. Findings: Data collected showed that the students generally accepted the interdisciplinary approach to project development. Factors such as project relevance, teamwork, time and schedule, and administration support, among others, affect team performance towards project completion. In the case of the Computer Science students, results show that students have learned skills during the experience that, as literature reveal, can only be acquired or mastered in their future profession as software engineers. Recommendations for Practitioners: The active collaboration of the industry with the University and the involvement of the other related courses in teaching software engineering methods are critical to the development of the students, not only in learning the methodology but also as a working professional. Recommendation for Researchers: It is interesting to know and eventually understand the interactions between interdisciplinary team members in the conduct of Software Engineering practices while working on their projects. More specifically, what creative tensions arise and how do the interdisciplinary teams handle the discourse? Impact on Society: This study bridges the gap between how Software Engineering is taught in the university and how Software Engineering teams work in real life. Future Research: Future research is targeted at refining and elaborating the elements of the interdisciplinary framework presented in this paper towards an integrated course module for Software Engineering education.

Aim/Purpose: This study investigates the variations in student participation patterns across different types of instructional activities, learning modes, and with different instructional guidance approaches. In the current study, different variables, modes of learning (guided versus unguided), and types of guidance (social versus cognitive) were manipulated in a series of microblogging-supported collaborative learning tasks to examine to what extent and in which aspects instructional guidance affects the effectiveness and student perception of microblogging-supported learning. Background: Despite the overwhelming agreement on the importance of instructional guidance in microblogging-supported learning environments, very few studies have been done to examine the specificity of guidance, such as how to structure and support microblogging activities, as well as what types of guidance are appropriate in what learning contexts. Methodology: This semester-long study utilized a case-study research design via a multi-dimensional approach in a hybrid classroom with both face-to-face and online environments. Tweets were collected from four types of activities and coded based on content within their contextual setting. Twenty-four college students participated in the study. Contribution: In response to the call to improve social media learning environments under-scored in contemporary education, the current case study took an initial step aiming at deepening the understanding of the role of instructional guidance in microblogging-supported learning environments. Findings: This study showcases that with instructor facilitation, students succeeded in being engaged in a highly participatory and interactive learning experience across a variety of tasks and activities. This study indicates that students’ perspectives of social media tools rely heavily on what instructors do with the tool and how the instructional activities are structured and supported. Instructors’ scaffolding and support is instrumental in keeping students on task and engaging students with meaningful events, thus ensuring the success of microblogging-based learning activities. Meanwhile, students’ perception of usefulness of instructional guidance is closely related to their own pre-perception and experience. Recommendations for Practitioners: When incorporating social media tools, it is important to examine learner’s prior knowledge and comfort level with these tools and tailor the design of instructional activities to their attributes. It is also vital to monitor student progress, adjust the type and amount of guidance and scaffolding provided as they progress, and eventually remove the scaffolding until students can demonstrate that they can perform the task successfully without assistance. Recommendation for Researchers: Due to many other potential factors in place that could potentially influence student learning, no conclusive remarks can be made regarding the superiority of either one type of guidance approach. Future researchers should continue to develop robust research methodologies to seek ways to better operationalize this variable and strive to understand its effect. Future Research: Future replication studies in other settings, with a larger sample size, and different populations will certainly provide further insights on the effects of instructional guidance in microblogging-based learning. Alternative coding methods may also shed light on differences in student interaction in terms of content diversity and depth of learning when analyzing the tweets. Advanced data collection techniques may be explored to ascertain the completeness of data collection.

Aim/Purpose: This paper presents a study about changes in computer science and software engineering students’ perceptions of their soft skills during their progress through the Computer Science Soft Skills course. Background: Soft skills are often associated with a person’s social, emotional and cognitive capabilities. Soft skills are increasingly sought out and are well recognized by employers alongside standard qualifications. Therefore, high importance is attributed to soft skills in computer science and software engineering education. Methodology: Content analysis was applied to interpret, categorize and code statements from students’ course assignment answers. Data analysis was performed gradually at the three main stages of the course and by the two students’ study populations. Contribution: The paper highlights the variety of (a) soft skills that can be learnt in one course, both on the individual level and on the team level and (b) assignments that can be given to students to increase their awareness and motivation to practice and learn soft skills. Findings: Data analysis revealed the following: (a) five individual soft skills categories, with 95 skills, and five team-related soft skills categories, with 52 skills (in total, the students mentioned 147 soft skills); (b) course assignments and particularly team-based activities elicited student awareness of their individual soft skills, both as strengths and weaknesses; (c) students developed their reflection skills, particularly with respect to team-related soft skills; and (d) significant differences exist between the two groups of students in several categories. Recommendations for Practitioners: It is important to provide undergraduate students with opportunities to integrate soft skills during their training. Establishing a meaningful learning process, such as project-based learning, enables students to apply and develop soft skills when accompanied by reflective thought processes. Recommendation for Researchers: A similar course can be taught and be accompanied by similar analysis of students’ learning outcomes, to examine the influence of local culture on the characteristics of soft skills. Impact on Society: Increased awareness of soft skills in scientists and engineers’ undergraduate education. University graduates who will strengthen their variety of soft skills in their academic training process and will be more meaningful employees in the workplace and in society. Future Research: Our future research aims (a) to explore additional innovative ways to increase students’ learning processes, awareness and practices in relation to soft skills and (b) to research how students’ soft skills are developed during the entire undergraduate studies both on the individual level and the team level.

Aim/Purpose: Multi-threaded software design is considered to be difficult, especially to novice programmers. In this study, we explored how students cope with a task that its solution requires a multi-threaded architecture to achieve optimal runtime. Background: An efficient exploit of multicore processors architecture requires computer programs that use parallel programming techniques. However, parallel programming is difficult to understand and apply by novice programmers. Methodology: The students had to address a two-stage problem: (1) design an optimal runtime solution to a given problem with no additional instructions; and (2) provide an optimal runtime multi-threaded design to the same problem. Interviews were conducted with a representative group of students to understand the underlying causes of their provided designs. We used qualitative research methods to gain refined insights regarding the students’ decision making during the design process. To analyze the gained data, we used content analysis tools. Contribution: The case study presented in this paper will help the teacher to stress the merits and limitations of various parallel architectures and confront students with the consequences of their solutions via performances’ benchmark. Findings: Analysis of the student’s solutions to the first stage revealed that the majority of them did not provide a multi-threaded solution ignoring the optimal runtime requirement. At the second stage, seven various architectures were provided differing in the number of involved threads, the data structures used, and the synchronization mechanism employed. The majority of the solutions were sub-optimal and only a few students provided an optimal one. Recommendations for Practitioners: We recommend conducting class discussions that will follow a task similar to the one used in this study. Recommendation for Researchers: To be able to generalize the received results this research should be repeated with larger study participant groups from various academic institutions. Impact on Society: Understanding the difficulties of novice programmers may lead to quality software systems. Future Research: To be able to generalize the received results this research should be repeated with larger study participant groups from various academic institutions.

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: 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: 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 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.

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.

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.

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.

A well-documented architecture can greatly improve comprehension and maintainability. However, shorter release cycles and quick delivery patterns results in negligence of architecture. In such situations, the architecture can be recovered from its current implementation based on considering dependency relations. In literature, structural and semantic dependencies are commonly used software features, and directory information along with co-change/change history information are among rarely utilised software features. But, they are found to help improve architecture recovery. Therefore, we consider investigating various features that may further improve the accuracy of existing architecture recovery techniques and evaluate their feasibility by considering them in different pairs. We compared five state-of-the-art methods under different feature subsets. We identified that two of them commonly outperform others but surprisingly with low accuracy in some evaluations. Further, we propose a new subset of features that reflects more accurate user perceptions and hence, results in improving the accuracy of architecture recovery techniques.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.

Conventional intelligent traffic congestion discrimination methods mainly use GPS terminals to collect traffic congestion data, which is vulnerable to the influence of vehicle time distribution, resulting in poor final discrimination effect. Necessary to design a new intelligent traffic congestion discrimination method based on wireless sensor network front-end data collection. That is to use the front-end data acquisition technology of wireless sensor network to generate a front-end data acquisition platform to obtain intelligent traffic congestion data, and then design an intelligent traffic congestion discrimination algorithm based on traffic congestion rules so as to achieve intelligent traffic congestion discrimination. The experimental results show that the intelligent traffic congestion discrimination method designed based on the front-end data collection of wireless sensor network has good discrimination effect, the obtained discrimination data is more accurate, effective and has certain application value, which has made certain contributions to reducing the frequency of urban traffic accidents.

In the perspective of institutional theory, business education is an institutional field, in which two major institutional forces are accreditations and rankings. In this context, French business schools (BS) have adopted an isomorphic response by starting to engage in research and publishing in academic journals. Studies have discussed their research as a new institutional trajectory. However, what remains unknown is how they differ from each other in such research dynamics. To bring new insights to the discussion, this quantitative study examines, over the period of 2008-2018, the evolution of research of French BS by systematically comparing the 'best' schools with other schools in all analyses. The results indicate a strong isomorphism in terms of publication quantity and productivity, scale of research collaboration and the internationalisation of research. However, these schools are heterogeneous in terms research quality and scale of international research collaboration, reflecting the diversity in their research strategy.

Though there have been many approaches to dealing with social problems in recent years, the concepts of social value have yet to be discussed thoroughly. Upon examining these concepts in existing studies and testing them with two case studies, the article shows that there is the possibility that a group's shared wants may not be widely recognised as a social problem, and targeting these unserved populations is a precondition for solving social issues. It is essential to identify hidden social problems by understanding what is still left, the number of people sharing the same want, the severity of the unmet want, and the possible resources for solution generation. Social value in its narrower definition means meeting the satisfaction of the group sharing the same want, while in its broader definition, it means meeting the satisfaction of wider society. Finding workable solutions involves not only the group of people sharing the same want but also others who do not have the same want but who do recognise the importance of acknowledging the want of the subgroup.

In order to improve recommendation coverage, a personalised recommendation method for English online learning resources based on improved collaborative filtering algorithm is studied to enhance the comprehensiveness of personalised recommendation for learning resources. Use matrix decomposition to decompose the user English online learning resource rating matrix. Cluster low dimensional English online learning resources by improving the K-means clustering algorithm. Based on the clustering results, calculate the backfill value of English online learning resources and backfill the information matrix of low dimensional English online learning resources. Using an improved collaborative filtering algorithm to calculate the predicted score of learning resources, personalised recommendation of English online learning resources for users based on the predicted score. Experimental results have shown that this method can effectively backfill English online learning resources, and the resource backfilling effect is excellent, and it has a high recommendation coverage rate.

Due to the problems of low clustering accuracy and efficiency in traditional similar resource clustering methods, this paper studies an English MOOC similar resource clustering method based on grey correlation. Principal component analysis was used to extract similar resource features of English MOOC, and feature selection methods was used to pre-process similar resource features of English MOOC. On this basis, based on the grey correlation method, the pre-processed English MOOC similar resource features are standardised, and the correlation degree between different English MOOC similar resource features is calculated. The English MOOC similar resource correlation matrix is constructed to achieve English MOOC similar resource clustering. The experimental results show that the contour coefficient of the proposed method is closer to one, and the clustering accuracy of similar resources in English MOOC is as high as 94.2%, with a clustering time of only 22.3 ms.

In order to enhance the accuracy of teaching resource recommendation results and optimise user experience, a personalised recommendation method for English teaching resources on the MOOC platform based on data mining is proposed. First, the learner's evaluation of resources and resource attributes are abstracted into the same space, and resource tags are established using the Knowledge graph. Then, interest preference constraints are introduced to mine sequential patterns of user historical learning behaviour in the MOOC platform. Finally, a graph neural network is used to construct a recommendation model, which adjusts users' short-term and short-term interest parameters to achieve dynamic personalised teaching recommendation resources. The experimental results show that the accuracy and recall of the resource recommendation results of the research method are always higher than 0.9, the normalised sorting gain is always higher than 0.5.

In order to shorten the integration and sharing time of English teaching resources, a MOOC English online and offline mixed teaching resource integration model based on convolutional neural networks is proposed. The intelligent integration model of MOOC English online and offline hybrid teaching resources based on convolutional neural network is constructed. The intelligent integration unit of teaching resources uses the Arduino device recognition program based on convolutional neural network to complete the classification of hybrid teaching resources. Based on the classification results, an English online and offline mixed teaching resource library for Arduino device MOOC is constructed, to achieve intelligent integration of teaching resources. The experimental results show that when the regularisation coefficient is 0.00002, the convolutional neural network model has the best training effect and the fastest convergence speed. And the resource integration time of the method in this article should not exceed 2 s at most.

The value and utility of traditional knowledge in conserving and commercialising genetic resources are increasingly becoming apparent due to advances in biotechnology and bioprospecting. However, the absence of an international legally binding instrument within the WIPO system means that traditional knowledge associated with genetic resources is not sufficiently protected like other forms of intellectual property. This means that indigenous peoples and local communities (IPLCs) do not benefit from the commercial exploitation of these resources. The efficacy of domestic tools to protect traditional knowledge and in balancing the rights of IPLCs and intellectual property rights (IPRs) is still debated. This paper employs a doctrinal research methodology based on desktop research of international and regional law instruments and the Constitution of the Republic of South Africa, 1996, to determine the basis for balancing the protection of genetic resources and associated traditional knowledge with competing interests of IPLCs and IPRs in South Africa.

In order to improve the classification accuracy and online allocation accuracy of teaching resources and shorten the allocation time, this paper proposes a new online allocation method of college ideological and political curriculum teaching resources based on differential search algorithm. Firstly, the feedback parameter model of teaching resources cleaning is constructed to complete the cleaning of teaching resources. Secondly, according to the results of anti-interference consideration, the linear feature extraction of ideological and political curriculum teaching resources is carried out. Finally, the online allocation objective function of teaching resources for ideological and political courses is constructed, and the differential search algorithm is used to optimise the objective function to complete the online allocation of resources. The experimental results show that this method can accurately classify the teaching resources of ideological and political courses, and can shorten the allocation time, with the highest allocation accuracy of 97%.

Because of the problems of low mining precision and slow mining speed in traditional enterprise marketing investment data mining methods, a fast mining method for enterprise marketing investment databased on improved association rules is proposed. First, the enterprise marketing investment data is collected through the crawler framework, and then the collected data is cleaned. Then, the cleaned data features are extracted, and the correlation degree between features is calculated. Finally, according to the calculation results, all data items are used as constraints to reduce the number of frequent itemsets. A pruning strategy is designed in advance. Combined with the constraints, the Apriori algorithm of association rules is improved, and the improved algorithm is used to calculate all frequent itemsets, Obtain fast mining results of enterprise marketing investment data. The experimental results show that the proposed method is fast and accurate in data mining of enterprise marketing investment.

The European Union Rights Management Directive 2014/26/EU, provides regulatory oversight of European Union (EU) Collective Management Organizations (CMOs). However, the Directive has no provision indicating how members of EU CMOs may conduct non-financial audits of their CMO income and reporting. This paper addresses the problem of a lack of an audit method through a case study of the five writer members of the music group Duran Duran, who have been members of the UK's CMO for performing rights - the Performing Rights Society (PRS) for over 35 years. The paper argues a new audit CMO member method that can address the lacunae regarding the absence of CMO member right to audit a CMO and an applicable CMO audit method.

This research delves into the wealth effect of shareholders from bidding firms created by mergers and acquisitions (M&A) in China and India, two of the world's most populous nations. The study reveals that on average, M&A deals create wealth for shareholders of the acquiring firms, as determined by abnormal percentage returns in a five-day event window. Regarding the further classification of acquiring firms based on industry, the abnormal percentage returns vary in different sectors in both countries. In China, shareholders benefit in seven out of ten industries, while in India, they gain in five out of nine industries. Moreover, the stock markets' responses vary depending on the type of M&A in each country. Cross-industry M&A deals in China generate higher gains for shareholders than within-industry deals, whereas, in India, within-industry M&A deals generate higher gains.