Pub Date : 2023-10-16DOI: 10.1186/s41239-023-00423-4
Rabia Maqsood, Paolo Ceravolo, Muhammad Ahmad, Muhammad Shahzad Sarfraz
Abstract The heterogeneous data acquired by educational institutes about students’ careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of students’ performances, and rare attempts are made at the domain level that may benefit the educational institutes at large to gauge and improve their institutional effectiveness. Our work aims to fill this gap by examining students’ transcripts data for identifying similar groups of students and patterns that might associate with these different cohorts of students based on: (a) difficulty level of a course category, (b) formation of course trajectories, and, (c) transitioning of students between different performance groups. We have exploited descriptive data mining and visualization methods to analyze transcript data of 1398 undergraduate Computer Science students of a private university in Pakistan. The dataset includes students’ transcript data of 124 courses from nine distinct course categories. In the end, we have discussed our findings in detail, challenges, and, future work directions.
{"title":"Examining students’ course trajectories using data mining and visualization approaches","authors":"Rabia Maqsood, Paolo Ceravolo, Muhammad Ahmad, Muhammad Shahzad Sarfraz","doi":"10.1186/s41239-023-00423-4","DOIUrl":"https://doi.org/10.1186/s41239-023-00423-4","url":null,"abstract":"Abstract The heterogeneous data acquired by educational institutes about students’ careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of students’ performances, and rare attempts are made at the domain level that may benefit the educational institutes at large to gauge and improve their institutional effectiveness. Our work aims to fill this gap by examining students’ transcripts data for identifying similar groups of students and patterns that might associate with these different cohorts of students based on: (a) difficulty level of a course category, (b) formation of course trajectories, and, (c) transitioning of students between different performance groups. We have exploited descriptive data mining and visualization methods to analyze transcript data of 1398 undergraduate Computer Science students of a private university in Pakistan. The dataset includes students’ transcript data of 124 courses from nine distinct course categories. In the end, we have discussed our findings in detail, challenges, and, future work directions.","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136077604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-13DOI: 10.1186/s41239-023-00424-3
Ahmed Tlili, Juan Garzón, Soheil Salha, Ronghuai Huang, Lin Xu, Daniel Burgos, Mouna Denden, Orna Farrell, Robert Farrow, Aras Bozkurt, Tel Amiel, Rory McGreal, Aída López-Serrano, David Wiley
Abstract While several studies have investigated the various effects of open educational resources (OER) and open educational practices (OEP), few have focused on its connection to learning achievement. The related scientific literature is divided about the effects of OER and OEP with regards to their contribution to learning achievement. To address this tension, a meta-analysis and research synthesis of 25 studies ( N = 119,840 participants) was conducted to quantitatively investigate the effects of OER and OEP on students’ learning achievement. The analysis included course subject, level of education, intervention duration, sample size, geographical distribution, and research design as moderating variables of the obtained effects. The findings revealed that OER and OEP have a significant yet negligible ( g = 0.07, p < 0.001) effect. Additionally, the analysis found that the obtained effect can be moderated by several variables, including course subject, level of education and geographical distribution. The study findings can help various stakeholders (e.g., educators, instructional designers or policy makers) in understanding what might hinder OER and OEP effect on learning achievement, hence accommodating better learning outcomes and more effective interventions.
虽然有一些研究调查了开放教育资源(OER)和开放教育实践(OEP)的各种影响，但很少有人关注其与学习成就的联系。关于OER和OEP对学习成就的贡献，相关的科学文献存在分歧。为了解决这种紧张关系，我们对25项研究(N = 119,840名参与者)进行了荟萃分析和研究综合，以定量调查OER和OEP对学生学习成绩的影响。分析包括课程科目、教育水平、干预持续时间、样本量、地理分布和研究设计作为获得效果的调节变量。结果显示OER和OEP有显著但可忽略的差异(g = 0.07, p <0.001)的效果。此外，分析发现，所获得的效果可以被几个变量调节，包括课程科目，教育水平和地理分布。研究结果可以帮助不同的利益相关者(如教育工作者、教学设计师或政策制定者)了解什么可能阻碍OER和OEP对学习成绩的影响，从而适应更好的学习成果和更有效的干预措施。
{"title":"Are open educational resources (OER) and practices (OEP) effective in improving learning achievement? A meta-analysis and research synthesis","authors":"Ahmed Tlili, Juan Garzón, Soheil Salha, Ronghuai Huang, Lin Xu, Daniel Burgos, Mouna Denden, Orna Farrell, Robert Farrow, Aras Bozkurt, Tel Amiel, Rory McGreal, Aída López-Serrano, David Wiley","doi":"10.1186/s41239-023-00424-3","DOIUrl":"https://doi.org/10.1186/s41239-023-00424-3","url":null,"abstract":"Abstract While several studies have investigated the various effects of open educational resources (OER) and open educational practices (OEP), few have focused on its connection to learning achievement. The related scientific literature is divided about the effects of OER and OEP with regards to their contribution to learning achievement. To address this tension, a meta-analysis and research synthesis of 25 studies ( N = 119,840 participants) was conducted to quantitatively investigate the effects of OER and OEP on students’ learning achievement. The analysis included course subject, level of education, intervention duration, sample size, geographical distribution, and research design as moderating variables of the obtained effects. The findings revealed that OER and OEP have a significant yet negligible ( g = 0.07, p < 0.001) effect. Additionally, the analysis found that the obtained effect can be moderated by several variables, including course subject, level of education and geographical distribution. The study findings can help various stakeholders (e.g., educators, instructional designers or policy makers) in understanding what might hinder OER and OEP effect on learning achievement, hence accommodating better learning outcomes and more effective interventions.","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135805741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In the field of Science, Technology, Engineering, and Mathematics (STEM) education, which aims to cultivate problem-solving skills, accurately assessing learners' engagement remains a significant challenge. We present a solution to this issue with the Real-time Automated STEM Engagement Detection System (RASEDS). This innovative system capitalizes on the power of artificial intelligence, computer vision, and the Interactive, Constructive, Active, and Passive (ICAP) framework. RASEDS uses You Only Learn One Representation (YOLOR) to detect and map learners' interactions onto the four levels of engagement delineated in the ICAP framework. This process informs the system's recommendation of adaptive learning materials, designed to boost both engagement and self-efficacy in STEM activities. Our study affirms that RASEDS accurately gauges engagement, and that the subsequent use of these adaptive materials significantly enhances both engagement and self-efficacy. Importantly, our research suggests a connection between elevated self-efficacy and increased engagement. As learners become more engaged in their learning process, their confidence is bolstered, thereby augmenting self-efficacy. We underscore the transformative potential of AI in facilitating adaptive learning in STEM education, highlighting the symbiotic relationship between engagement and self-efficacy.
在旨在培养解决问题能力的科学、技术、工程和数学(STEM)教育领域，准确评估学习者的参与程度仍然是一个重大挑战。我们提出了一种解决方案，即实时自动化STEM接合检测系统(RASEDS)。这个创新的系统利用了人工智能、计算机视觉和交互式、建设性、主动和被动(ICAP)框架的力量。RASEDS使用You Only Learn One Representation (YOLOR)来检测学习者的互动，并将其映射到ICAP框架中描述的四个参与层次。这一过程为系统推荐适应性学习材料提供了信息，旨在提高STEM活动的参与度和自我效能感。我们的研究证实，RASEDS准确地测量了投入度，随后使用这些适应性材料显著提高了投入度和自我效能感。重要的是，我们的研究表明，自我效能感的提升和参与度的提高之间存在联系。随着学习者在学习过程中变得更加投入，他们的信心得到了增强，从而增强了自我效能感。我们强调人工智能在促进STEM教育中的适应性学习方面的变革潜力，强调参与与自我效能之间的共生关系。
{"title":"Leveraging computer vision for adaptive learning in STEM education: effect of engagement and self-efficacy","authors":"Ting-Ting Wu, Hsin-Yu Lee, Wei-Sheng Wang, Chia-Ju Lin, Yueh-Min Huang","doi":"10.1186/s41239-023-00422-5","DOIUrl":"https://doi.org/10.1186/s41239-023-00422-5","url":null,"abstract":"Abstract In the field of Science, Technology, Engineering, and Mathematics (STEM) education, which aims to cultivate problem-solving skills, accurately assessing learners' engagement remains a significant challenge. We present a solution to this issue with the Real-time Automated STEM Engagement Detection System (RASEDS). This innovative system capitalizes on the power of artificial intelligence, computer vision, and the Interactive, Constructive, Active, and Passive (ICAP) framework. RASEDS uses You Only Learn One Representation (YOLOR) to detect and map learners' interactions onto the four levels of engagement delineated in the ICAP framework. This process informs the system's recommendation of adaptive learning materials, designed to boost both engagement and self-efficacy in STEM activities. Our study affirms that RASEDS accurately gauges engagement, and that the subsequent use of these adaptive materials significantly enhances both engagement and self-efficacy. Importantly, our research suggests a connection between elevated self-efficacy and increased engagement. As learners become more engaged in their learning process, their confidence is bolstered, thereby augmenting self-efficacy. We underscore the transformative potential of AI in facilitating adaptive learning in STEM education, highlighting the symbiotic relationship between engagement and self-efficacy.","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135132301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-25DOI: 10.1186/s41239-023-00421-6
Taibe Kulaksız
Abstract This study is purposed to implement and test a praxeological learning approach to enhance pre-service EFL teachers’ technological pedagogical content knowledge and online information-seeking skills. This study was conducted based on a convergent parallel mixed design involving thirty-seven sophomore pre-service EFL teachers. Multiple data collection tools were administered at the beginning and end of the course, and data were analyzed aligning with quantitative and qualitative methods complementarily. Active and decisive participation of the pre-service teachers shaped the course design following the sections of independent study, context orientation, and context-based study within the Technological Pedagogical Content Knowledge Framework. Findings showed that pre-service teachers’ technological pedagogical content knowledge and online information-seeking strategies of evaluation, selecting main ideas, and trial & error were significantly improved. Praxeological learning, following the Technological Pedagogical Content Knowledge Framework step-by-step and highlighting context-sensitivity, scaffolded pre-service teachers’ knowledge construction cumulatively and provided them with authentic learning experiences. The praxeological learning approach can support long-term motivation for technology integration knowledge and skills acquisition for pre-service teachers’ future careers.
{"title":"Praxeological learning approach in the development of pre-service EFL teachers' TPACK and online information-seeking strategies","authors":"Taibe Kulaksız","doi":"10.1186/s41239-023-00421-6","DOIUrl":"https://doi.org/10.1186/s41239-023-00421-6","url":null,"abstract":"Abstract This study is purposed to implement and test a praxeological learning approach to enhance pre-service EFL teachers’ technological pedagogical content knowledge and online information-seeking skills. This study was conducted based on a convergent parallel mixed design involving thirty-seven sophomore pre-service EFL teachers. Multiple data collection tools were administered at the beginning and end of the course, and data were analyzed aligning with quantitative and qualitative methods complementarily. Active and decisive participation of the pre-service teachers shaped the course design following the sections of independent study, context orientation, and context-based study within the Technological Pedagogical Content Knowledge Framework. Findings showed that pre-service teachers’ technological pedagogical content knowledge and online information-seeking strategies of evaluation, selecting main ideas, and trial & error were significantly improved. Praxeological learning, following the Technological Pedagogical Content Knowledge Framework step-by-step and highlighting context-sensitivity, scaffolded pre-service teachers’ knowledge construction cumulatively and provided them with authentic learning experiences. The praxeological learning approach can support long-term motivation for technology integration knowledge and skills acquisition for pre-service teachers’ future careers.","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135770909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-04DOI: 10.1186/s41239-023-00420-7
Chengming Zhang, Jessica Schießl, Lea Plößl, Florian Hofmann, M. Gläser-Zikuda
{"title":"Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis","authors":"Chengming Zhang, Jessica Schießl, Lea Plößl, Florian Hofmann, M. Gläser-Zikuda","doi":"10.1186/s41239-023-00420-7","DOIUrl":"https://doi.org/10.1186/s41239-023-00420-7","url":null,"abstract":"","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":" ","pages":""},"PeriodicalIF":8.6,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46059188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-28DOI: 10.1186/s41239-023-00419-0
Dirk Ifenthaler, Martin Cooper, L. Daniela, Muhittin Şahin
{"title":"Social anxiety in digital learning environments: an international perspective and call to action","authors":"Dirk Ifenthaler, Martin Cooper, L. Daniela, Muhittin Şahin","doi":"10.1186/s41239-023-00419-0","DOIUrl":"https://doi.org/10.1186/s41239-023-00419-0","url":null,"abstract":"","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":" ","pages":""},"PeriodicalIF":8.6,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47508467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-22DOI: 10.1186/s41239-023-00417-2
Faming Wang, Ronnel B. King, C. Chai, Ying Zhou
{"title":"University students’ intentions to learn artificial intelligence: the roles of supportive environments and expectancy–value beliefs","authors":"Faming Wang, Ronnel B. King, C. Chai, Ying Zhou","doi":"10.1186/s41239-023-00417-2","DOIUrl":"https://doi.org/10.1186/s41239-023-00417-2","url":null,"abstract":"","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":" ","pages":"1-21"},"PeriodicalIF":8.6,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46834672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-18DOI: 10.1186/s41239-023-00416-3
J. Lewohl
{"title":"Exploring student perceptions and use of face-to-face classes, technology-enhanced active learning, and online resources","authors":"J. Lewohl","doi":"10.1186/s41239-023-00416-3","DOIUrl":"https://doi.org/10.1186/s41239-023-00416-3","url":null,"abstract":"","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":" ","pages":"1-17"},"PeriodicalIF":8.6,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46313882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-14DOI: 10.1186/s41239-023-00418-1
Zhongling Pi, Yi Zhang, Qiuchen Yu, Jiumin Yang
{"title":"A familiar peer improves students’ behavior patterns, attention, and performance when learning from video lectures","authors":"Zhongling Pi, Yi Zhang, Qiuchen Yu, Jiumin Yang","doi":"10.1186/s41239-023-00418-1","DOIUrl":"https://doi.org/10.1186/s41239-023-00418-1","url":null,"abstract":"","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"20 1","pages":"1-21"},"PeriodicalIF":8.6,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43762296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Students’ satisfaction with online courses is considered as one of the most critical components in the continued use, as well as, adoption of e-learning applications. The study aimed at determining and analyzing the constructs that affect students’ satisfaction. It examined the effect of students’ self-efficacy and the quality of course design on students’ satisfaction, mediated by their attitudes toward online courses. The study was conducted at University of Ha’il. Responses of 202 students were used for the data analysis. The collected data was analyzed using two steps in AMOS: The proposed measurement model was developed using confirmatory factor analysis (CFA), and the relationships were examined using structural equation modeling (SEM). The results revealed that both students’ self-efficacy and the quality of course design had a significant positive effect on students’ satisfaction, mediated by their attitudes towards online courses. The outcomes of this study can help decision-makers and policymakers in higher education take essential steps to enhance students’ satisfaction with online courses and ensure that they continue to be used.
{"title":"The Effect of Self-efficacy and Course Design Quality on Students’ Satisfaction with Online Courses: A Structural Equation Modeling Approach","authors":"S. Alshammari, A. Z. Almankory, M. Alshammari","doi":"10.46328/ijte.549","DOIUrl":"https://doi.org/10.46328/ijte.549","url":null,"abstract":"Students’ satisfaction with online courses is considered as one of the most critical components in the continued use, as well as, adoption of e-learning applications. The study aimed at determining and analyzing the constructs that affect students’ satisfaction. It examined the effect of students’ self-efficacy and the quality of course design on students’ satisfaction, mediated by their attitudes toward online courses. The study was conducted at University of Ha’il. Responses of 202 students were used for the data analysis. The collected data was analyzed using two steps in AMOS: The proposed measurement model was developed using confirmatory factor analysis (CFA), and the relationships were examined using structural equation modeling (SEM). The results revealed that both students’ self-efficacy and the quality of course design had a significant positive effect on students’ satisfaction, mediated by their attitudes towards online courses. The outcomes of this study can help decision-makers and policymakers in higher education take essential steps to enhance students’ satisfaction with online courses and ensure that they continue to be used.","PeriodicalId":13871,"journal":{"name":"International Journal of Educational Technology in Higher Education","volume":"16 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88164021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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