Pub Date : 2025-04-15DOI: 10.1016/j.caeo.2025.100256
Ilse Hagerer
Leadership competencies become increasingly important for realizing disruptive technologies but are rarely taught at universities in science, technology, engineering, and mathematics (STEM) fields. Due to the threatening skills shortage and the prevailing gender gap in STEM, especially in leadership positions, it is vital to engage women and to improve leadership competencies for STEM professionals in the long term during their jobs or studies with a low entrance barrier. To address this issue, we developed PlayMINT—the first serious learning game for leadership competencies relevant to 21st-century challenges. We comprehensively evaluated PlayMINT in a rigorous randomized long-term user experiment including a control group using traditional learning methods over nine months with a substantial sample size of 181 female STEM students from German universities. Moreover, we used a multi-method approach combining self-assessments and learning analytics. Despite the low entrance barrier, the leadership competencies gained through PlayMINT were equivalent to those obtained through traditional learning methods. PlayMINT enabled significant improvements in innovative work behavior, creative self-efficacy, effective communication, empowerment, envisioning, and business knowledge of participants over time.
{"title":"PlayMINT—an effective digital learning game for leadership competencies of female STEM students","authors":"Ilse Hagerer","doi":"10.1016/j.caeo.2025.100256","DOIUrl":"10.1016/j.caeo.2025.100256","url":null,"abstract":"<div><div>Leadership competencies become increasingly important for realizing disruptive technologies but are rarely taught at universities in science, technology, engineering, and mathematics (STEM) fields. Due to the threatening skills shortage and the prevailing gender gap in STEM, especially in leadership positions, it is vital to engage women and to improve leadership competencies for STEM professionals in the long term during their jobs or studies with a low entrance barrier. To address this issue, we developed PlayMINT—the first serious learning game for leadership competencies relevant to 21st-century challenges. We comprehensively evaluated PlayMINT in a rigorous randomized long-term user experiment including a control group using traditional learning methods over nine months with a substantial sample size of 181 female STEM students from German universities. Moreover, we used a multi-method approach combining self-assessments and learning analytics. Despite the low entrance barrier, the leadership competencies gained through PlayMINT were equivalent to those obtained through traditional learning methods. PlayMINT enabled significant improvements in innovative work behavior, creative self-efficacy, effective communication, empowerment, envisioning, and business knowledge of participants over time.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100256"},"PeriodicalIF":4.1,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-14DOI: 10.1016/j.caeo.2025.100257
Sandra Drumm
Learning paths (LP), a combination of internet-based, sequenced learning content and self-learning tasks, enable learning to take place according to individual pace and depth and offer automated tests to check one’s own learning process. A broad diversity in learning approaches within LPs can help heterogeneous student groups to acquire the same knowledge base for further instruction and can be useful in developing blended learning courses. It turns out however, that different students show varying degrees of success when working autonomously with digital learning paths. Based on this, the following questions arise: how do students engage with the digital content; which learning opportunities do the students notice, and how do they use them. The study conducted examined student statements on how they worked through a learning path and why they chose a certain approach. Additionally, students answered questions about their process in a stimulated recall setting in order to find out why they processed the path in a certain way. The results show that success in the course is highly dependent on how much students were able to activate their self-regulating learning skills. Being able to apply their own strategies and working habits helped well-performing students, while the same setting offered too much openness and thus confusion to weaker-performing students. This provides key information on fostering engagement and self-regulated student learning, and how access to lectures for independent study can be implemented in a flipped classroom scenario.
{"title":"Applying individual strategies enhances learning in asynchronous learning paths","authors":"Sandra Drumm","doi":"10.1016/j.caeo.2025.100257","DOIUrl":"10.1016/j.caeo.2025.100257","url":null,"abstract":"<div><div>Learning paths (LP), a combination of internet-based, sequenced learning content and self-learning tasks, enable learning to take place according to individual pace and depth and offer automated tests to check one’s own learning process. A broad diversity in learning approaches within LPs can help heterogeneous student groups to acquire the same knowledge base for further instruction and can be useful in developing blended learning courses. It turns out however, that different students show varying degrees of success when working autonomously with digital learning paths. Based on this, the following questions arise: how do students engage with the digital content; which learning opportunities do the students notice, and how do they use them. The study conducted examined student statements on how they worked through a learning path and why they chose a certain approach. Additionally, students answered questions about their process in a stimulated recall setting in order to find out why they processed the path in a certain way. The results show that success in the course is highly dependent on how much students were able to activate their self-regulating learning skills. Being able to apply their own strategies and working habits helped well-performing students, while the same setting offered too much openness and thus confusion to weaker-performing students. This provides key information on fostering engagement and self-regulated student learning, and how access to lectures for independent study can be implemented in a flipped classroom scenario.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100257"},"PeriodicalIF":4.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-30DOI: 10.1016/j.caeo.2025.100250
Daniel G. Ferguson, Caitlin Campbell, Zachary L. Nolen, Kristy L. Daniel
Social media has become a major force in the internet age and has gained much interest as a potential new educational tool. Currently, many instructors assume that students have positive perceptions of using social media in their courses. However, there is no instrument that can assess student perceptions of social media use in academic courses. We created and tested the perceptions of social media (POSoM) questionnaire and determined its factorability through an exploratory factor analysis. Using Cronbach's alpha, we confirmed the reliability of our four factors. We found that the POSoM questionnaire contained four reliable factors: Academic Perceptions, Academic Usage, Academic Communication, and Personal Usage. Using the POSoM questionnaire, we found that students do not want to communicate in academic settings through social media and are apathetic to use of social media for other academic uses. Our results provide a new reliable instrument that can be used to further explore students’ perceptions of social media in science courses.
{"title":"Considering and measuring student perceptions on the role of using social media as an educational tool in science courses","authors":"Daniel G. Ferguson, Caitlin Campbell, Zachary L. Nolen, Kristy L. Daniel","doi":"10.1016/j.caeo.2025.100250","DOIUrl":"10.1016/j.caeo.2025.100250","url":null,"abstract":"<div><div>Social media has become a major force in the internet age and has gained much interest as a potential new educational tool. Currently, many instructors assume that students have positive perceptions of using social media in their courses. However, there is no instrument that can assess student perceptions of social media use in academic courses. We created and tested the perceptions of social media (POSoM) questionnaire and determined its factorability through an exploratory factor analysis. Using Cronbach's alpha, we confirmed the reliability of our four factors. We found that the POSoM questionnaire contained four reliable factors: Academic Perceptions, Academic Usage, Academic Communication, and Personal Usage. Using the POSoM questionnaire, we found that students do not want to communicate in academic settings through social media and are apathetic to use of social media for other academic uses. Our results provide a new reliable instrument that can be used to further explore students’ perceptions of social media in science courses.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100250"},"PeriodicalIF":4.1,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-29DOI: 10.1016/j.caeo.2025.100253
Kyungbin Kwon , Sang Joon Lee , Keunjae Kim
This study conducts a systematic review of the literature to investigate gender disparities in K-12 computer science (CS) education. We selected articles published in peer-reviewed journals that focused on both cognitive and affective aspects of computational thinking and CS education at the primary and secondary levels. A total of 29 studies were reviewed, and their findings were synthesized to assess the status of gender disparities, contributing factors, and instructional approaches. The results indicated that gender differences in cognitive and affective dimensions of CS education become more evident as students advance through school, with a greater negative impact on girls. The review identified three interconnected factors contributing to these disparities: socio-cultural influences, educational environments, and individual psychological factors. Additionally, the study proposed instructional approaches to address these issues and recommended future research to fill the current gaps in CS education research.
{"title":"Gender Disparities in K-12 Computer Science Education: Status, Contributing Factors, and Instructional Approaches","authors":"Kyungbin Kwon , Sang Joon Lee , Keunjae Kim","doi":"10.1016/j.caeo.2025.100253","DOIUrl":"10.1016/j.caeo.2025.100253","url":null,"abstract":"<div><div>This study conducts a systematic review of the literature to investigate gender disparities in K-12 computer science (CS) education. We selected articles published in peer-reviewed journals that focused on both cognitive and affective aspects of computational thinking and CS education at the primary and secondary levels. A total of 29 studies were reviewed, and their findings were synthesized to assess the status of gender disparities, contributing factors, and instructional approaches. The results indicated that gender differences in cognitive and affective dimensions of CS education become more evident as students advance through school, with a greater negative impact on girls. The review identified three interconnected factors contributing to these disparities: socio-cultural influences, educational environments, and individual psychological factors. Additionally, the study proposed instructional approaches to address these issues and recommended future research to fill the current gaps in CS education research.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100253"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-29DOI: 10.1016/j.caeo.2025.100254
Xueqing FANG , Thomas K.F. CHIU
Video creation provides students with opportunities to engage in authentic learning experiences while developing knowledge and 21st-century skills across various subjects. The student-created video activity could be an effective pedagogical approach for contemporary higher education teaching in the artificial intelligence (AI) Era. However, its full potential has yet to be realized, and more research is needed to explore learning methodologies that can enhance its effectiveness. Mind mapping (MM) and real-time commenting (RTC) are two strategies that have been shown to enhance student engagement. This study investigated the effects of MM (with vs. without) and RTC (with vs. without) on students’ need satisfaction, engagement, creativity, and collaboration, using Self-Determination Theory (SDT) to explain how the two strategies influence engagement and learning outcomes in video creation activities. We conducted an eight-week intervention study with 138 Chinese university students, using a 2 × 2 between-subjects factorial design, with four experimental groups: video creation (VC), video creation with MM (VC-MM), video creation with RTC (VC-RTC), and video creation with both MM and RTC (VC-MMRTC). Our analysis revealed that: (i) MM significantly satisfied students’ needs for autonomy, competence, and relatedness, while RTC significantly fulfilled their need for relatedness; (ii) MM significantly improved students’ behavioral, cognitive, and agentic engagement, while RTC significantly enhanced their emotional engagement; (iii) MM significantly improved students’ collaboration; and (iv) neither the MM nor RTC significantly improved students’ creativity. The results highlight the effectiveness of integrating MM and RTC strategies in satisfying students’ three psychological needs, enhancing four types of student engagement, and improving collaboration in video-based learning activities. With the help of generative AI tools, instructors and students can easily adopt these strategies for effective learning.
{"title":"Using Self-Determination Theory to Explain How Mind Mapping and Real-time Commenting Enhance Student Engagement and Learning Outcomes in Video Creation","authors":"Xueqing FANG , Thomas K.F. CHIU","doi":"10.1016/j.caeo.2025.100254","DOIUrl":"10.1016/j.caeo.2025.100254","url":null,"abstract":"<div><div>Video creation provides students with opportunities to engage in authentic learning experiences while developing knowledge and 21st-century skills across various subjects. The student-created video activity could be an effective pedagogical approach for contemporary higher education teaching in the artificial intelligence (AI) Era. However, its full potential has yet to be realized, and more research is needed to explore learning methodologies that can enhance its effectiveness. Mind mapping (MM) and real-time commenting (RTC) are two strategies that have been shown to enhance student engagement. This study investigated the effects of MM (with vs. without) and RTC (with vs. without) on students’ need satisfaction, engagement, creativity, and collaboration, using Self-Determination Theory (SDT) to explain how the two strategies influence engagement and learning outcomes in video creation activities. We conducted an eight-week intervention study with 138 Chinese university students, using a 2 × 2 between-subjects factorial design, with four experimental groups: video creation (VC), video creation with MM (VC-MM), video creation with RTC (VC-RTC), and video creation with both MM and RTC (VC-MMRTC). Our analysis revealed that: (i) MM significantly satisfied students’ needs for autonomy, competence, and relatedness, while RTC significantly fulfilled their need for relatedness; (ii) MM significantly improved students’ behavioral, cognitive, and agentic engagement, while RTC significantly enhanced their emotional engagement; (iii) MM significantly improved students’ collaboration; and (iv) neither the MM nor RTC significantly improved students’ creativity. The results highlight the effectiveness of integrating MM and RTC strategies in satisfying students’ three psychological needs, enhancing four types of student engagement, and improving collaboration in video-based learning activities. With the help of generative AI tools, instructors and students can easily adopt these strategies for effective learning.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100254"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-29DOI: 10.1016/j.caeo.2025.100249
Noble Lo , Alan Wong , Sumie Chan
This study investigates the effect of AI-generated feedback on university students’ essay writing proficiency in Hong Kong. By integrating generative AI into the revision process, the research examines how automated feedback influences the quality of students’ written work, as well as their engagement, motivation, and emotional responses during revision. The study employs a randomized controlled design, comparing students who received AI feedback on their essays with those who did not. Both quantitative and qualitative data were collected to assess the impact of AI feedback on writing improvement and student experiences. Quantitative analysis shows significant improvements in essay quality for students who utilized AI feedback, while qualitative findings highlight increased engagement and motivation, though students exhibited mixed emotional responses to the revision process. The results suggest that generative AI has considerable potential to enhance writing skills in higher education by providing timely, individualized feedback. This research contributes to ongoing discussions on the role of AI in education, particularly in supporting language instruction and student development.
{"title":"The impact of generative AI on essay revisions and student engagement","authors":"Noble Lo , Alan Wong , Sumie Chan","doi":"10.1016/j.caeo.2025.100249","DOIUrl":"10.1016/j.caeo.2025.100249","url":null,"abstract":"<div><div>This study investigates the effect of AI-generated feedback on university students’ essay writing proficiency in Hong Kong. By integrating generative AI into the revision process, the research examines how automated feedback influences the quality of students’ written work, as well as their engagement, motivation, and emotional responses during revision. The study employs a randomized controlled design, comparing students who received AI feedback on their essays with those who did not. Both quantitative and qualitative data were collected to assess the impact of AI feedback on writing improvement and student experiences. Quantitative analysis shows significant improvements in essay quality for students who utilized AI feedback, while qualitative findings highlight increased engagement and motivation, though students exhibited mixed emotional responses to the revision process. The results suggest that generative AI has considerable potential to enhance writing skills in higher education by providing timely, individualized feedback. This research contributes to ongoing discussions on the role of AI in education, particularly in supporting language instruction and student development.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100249"},"PeriodicalIF":5.7,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-25DOI: 10.1016/j.caeo.2025.100251
Fitsum Gizachew Deriba, Ismaila Temitayo Sanusi
In light of the ongoing discourse on integrating artificial intelligence (AI) into formal education systems, it is imperative to examine both curriculum and teaching practices, particularly in developing regions. This study explores the Information Communication and Technology (ICT) curriculum of Ethiopian secondary schools to identify AI-related content within the learning guide. Additionally, it assesses ICT educators' knowledge, practices, challenges, and recommendations for effectively implementing AI in Ethiopian schools. Employing a qualitative approach, this study reviewed AI content in the Ethiopian secondary school ICT curriculum and conducted audio-recorded interviews with 10 ICT teachers. Document analysis and thematic analysis were utilized to interpret the collected data. The AI content in the curriculum was analyzed and findings were discussed within the framework of the Five Big Ideas in AI. Our findings reveal that the AI content in the Ethiopian secondary school ICT curriculum is predominantly definitional. The thematic analysis of teacher interview data highlights the methods employed in teaching AI, including pedagogical challenges such as limited understanding of AI concepts. Furthermore, several recommendations emerged for the effective implementation of AI in schools, including curriculum revisions to incorporate AI topics in early childhood and primary education, as well as professional development opportunities. We also discuss the implications, limitations, and future research directions of this study.
{"title":"Artificial intelligence in Ethiopian school curriculum: Educators' practices, challenges, and recommendations","authors":"Fitsum Gizachew Deriba, Ismaila Temitayo Sanusi","doi":"10.1016/j.caeo.2025.100251","DOIUrl":"10.1016/j.caeo.2025.100251","url":null,"abstract":"<div><div>In light of the ongoing discourse on integrating artificial intelligence (AI) into formal education systems, it is imperative to examine both curriculum and teaching practices, particularly in developing regions. This study explores the Information Communication and Technology (ICT) curriculum of Ethiopian secondary schools to identify AI-related content within the learning guide. Additionally, it assesses ICT educators' knowledge, practices, challenges, and recommendations for effectively implementing AI in Ethiopian schools. Employing a qualitative approach, this study reviewed AI content in the Ethiopian secondary school ICT curriculum and conducted audio-recorded interviews with 10 ICT teachers. Document analysis and thematic analysis were utilized to interpret the collected data. The AI content in the curriculum was analyzed and findings were discussed within the framework of the Five Big Ideas in AI. Our findings reveal that the AI content in the Ethiopian secondary school ICT curriculum is predominantly definitional. The thematic analysis of teacher interview data highlights the methods employed in teaching AI, including pedagogical challenges such as limited understanding of AI concepts. Furthermore, several recommendations emerged for the effective implementation of AI in schools, including curriculum revisions to incorporate AI topics in early childhood and primary education, as well as professional development opportunities. We also discuss the implications, limitations, and future research directions of this study.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100251"},"PeriodicalIF":4.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-12DOI: 10.1016/j.caeo.2025.100246
Thomas Schubatzky , Jan-Philipp Burde , Rike Große-Heilmann , Andreas Lachner , Josef Riese , David Weiler
Educational technology (ET) is playing an increasingly important role in classrooms and has the potential to support student learning. However, teachers need to implement ET in a purposeful way. A necessary –but insufficient –condition for meaningful implementation of ET is the intention to use it in the first place. This study aims to investigate the predictors of pre-service teachers’ intention to use ET, specifically focusing on how technological pedagogical content knowledge (TPCK) interacts with the constructs of the Technology Acceptance Model (TAM). While previous research has frequently employed self-reported TPCK to explore these relationships, our study uses a test-based measure to provide a more objective assessment. We also aim to understand how these relationships evolve over time, particularly during a technology integration seminar in teacher education. Using path analysis including N = 146 preservice teachers, we examined the relationships between test-based TPCK, self-efficacy, and the TAM variables (perceived usefulness, perceived ease of use, and intention to use ET). Our findings indicate that self-efficacy is a strong predictor of perceived usefulness, perceived ease of integration, and intention to use ET, whereas TPCK primarily influences perceived usefulness and indirectly affects intention. Furthermore, we observed that the roles of TPCK and self-efficacy shift over time. This study contributes to a deeper understanding of how objective measures of professional knowledge can reshape interpretations of TAM studies and guide the design of teacher preparation programs.
{"title":"From knowledge to intention: The role of TPACK and self-efficacy in technology integration","authors":"Thomas Schubatzky , Jan-Philipp Burde , Rike Große-Heilmann , Andreas Lachner , Josef Riese , David Weiler","doi":"10.1016/j.caeo.2025.100246","DOIUrl":"10.1016/j.caeo.2025.100246","url":null,"abstract":"<div><div>Educational technology (ET) is playing an increasingly important role in classrooms and has the potential to support student learning. However, teachers need to implement ET in a purposeful way. A necessary –but insufficient –condition for meaningful implementation of ET is the intention to use it in the first place. This study aims to investigate the predictors of pre-service teachers’ intention to use ET, specifically focusing on how technological pedagogical content knowledge (TPCK) interacts with the constructs of the Technology Acceptance Model (TAM). While previous research has frequently employed self-reported TPCK to explore these relationships, our study uses a test-based measure to provide a more objective assessment. We also aim to understand how these relationships evolve over time, particularly during a technology integration seminar in teacher education. Using path analysis including N = 146 preservice teachers, we examined the relationships between test-based TPCK, self-efficacy, and the TAM variables (perceived usefulness, perceived ease of use, and intention to use ET). Our findings indicate that self-efficacy is a strong predictor of perceived usefulness, perceived ease of integration, and intention to use ET, whereas TPCK primarily influences perceived usefulness and indirectly affects intention. Furthermore, we observed that the roles of TPCK and self-efficacy shift over time. This study contributes to a deeper understanding of how objective measures of professional knowledge can reshape interpretations of TAM studies and guide the design of teacher preparation programs.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100246"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-12DOI: 10.1016/j.caeo.2025.100248
Nadia Catenazzi , Lorenzo Sommaruga , Kylene De Angelis , Sara Caboni
This paper proposes a comprehensive methodology to implement learning outcomes-based training and assessment, starting with the course planning, followed by the training delivery, and ending with the assessment and recognition of the achieved learning outcomes with the release of digital badges. The methodology consists of a number of steps organized in three main phases: curriculum development, micro-credentials and digital badge setting, training delivery and badge awarding. The methodology has been applied and refined in the context of Vocational Education and Training projects, enabling the creation of a learning outcomes-based modular curriculum, the creation of a constellation of digital badges based on the Open Badges standard, and the creation of an infrastructure for the release of digital badges. In the learning outcome journey, it represents a showcase of how intended and achieved learning outcomes can be aligned.
{"title":"A comprehensive methodology for curriculum development, training delivery and certification using learning outcomes and digital badges","authors":"Nadia Catenazzi , Lorenzo Sommaruga , Kylene De Angelis , Sara Caboni","doi":"10.1016/j.caeo.2025.100248","DOIUrl":"10.1016/j.caeo.2025.100248","url":null,"abstract":"<div><div>This paper proposes a comprehensive methodology to implement learning outcomes-based training and assessment, starting with the course planning, followed by the training delivery, and ending with the assessment and recognition of the achieved learning outcomes with the release of digital badges. The methodology consists of a number of steps organized in three main phases: curriculum development, micro-credentials and digital badge setting, training delivery and badge awarding. The methodology has been applied and refined in the context of Vocational Education and Training projects, enabling the creation of a learning outcomes-based modular curriculum, the creation of a constellation of digital badges based on the Open Badges standard, and the creation of an infrastructure for the release of digital badges. In the learning outcome journey, it represents a showcase of how intended and achieved learning outcomes can be aligned.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100248"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-02DOI: 10.1016/j.caeo.2025.100245
Solomon Sunday Oyelere , Kehinde Aruleba
In today's era of technological evolution, programming education is crucial for shaping the future workforce and fostering innovation. However, access to quality computer science education remains a significant challenge with Sub-Saharan Africa nations experiencing a pronounced digital divide. Despite growing interest in technology, these countries struggle with unequal access to educational resources. AI-driven tools like ChatGPT, Codey, and GitHub Copilot offer personalized learning experiences that could democratize access to knowledge and reshape programming education. This quantitative study examines the impact of these AI tools on fostering inclusive education in Kenya, Nigeria, and South Africa. It involves 322 university students, using purposive sampling and online questionnaires. Various quantitative analyzes, including descriptive statistics, country-wise comparisons, one-way ANOVA, Kruskal–Wallis tests, and correlation analysis, were conducted. The study reveals students’ motivations for programming, their attitudes towards AI-driven educational tools, and the perceived impact on equity, diversity, and inclusion. Significant variations were found in attitudes based on educational level and country of residence, highlighting the need for tailored strategies to enhance the inclusivity and effectiveness of AI-driven programming education tools.
{"title":"A comparative study of student perceptions on generative AI in programming education across Sub-Saharan Africa","authors":"Solomon Sunday Oyelere , Kehinde Aruleba","doi":"10.1016/j.caeo.2025.100245","DOIUrl":"10.1016/j.caeo.2025.100245","url":null,"abstract":"<div><div>In today's era of technological evolution, programming education is crucial for shaping the future workforce and fostering innovation. However, access to quality computer science education remains a significant challenge with Sub-Saharan Africa nations experiencing a pronounced digital divide. Despite growing interest in technology, these countries struggle with unequal access to educational resources. AI-driven tools like ChatGPT, Codey, and GitHub Copilot offer personalized learning experiences that could democratize access to knowledge and reshape programming education. This quantitative study examines the impact of these AI tools on fostering inclusive education in Kenya, Nigeria, and South Africa. It involves 322 university students, using purposive sampling and online questionnaires. Various quantitative analyzes, including descriptive statistics, country-wise comparisons, one-way ANOVA, Kruskal–Wallis tests, and correlation analysis, were conducted. The study reveals students’ motivations for programming, their attitudes towards AI-driven educational tools, and the perceived impact on equity, diversity, and inclusion. Significant variations were found in attitudes based on educational level and country of residence, highlighting the need for tailored strategies to enhance the inclusivity and effectiveness of AI-driven programming education tools.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"8 ","pages":"Article 100245"},"PeriodicalIF":4.1,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号