Pub Date : 2024-01-22DOI: 10.1080/15391523.2024.2304066
Lanqin Zheng, Yunchao Fan, Lei Gao, Zichen Huang, Bodong Chen, Miaolang Long
As an effective form of pedagogy, online collaborative learning has received increasing application in the field of education. However, learners often feel frustrated with regard to knowledge build...
{"title":"Using AI-empowered assessments and personalized recommendations to promote online collaborative learning performance","authors":"Lanqin Zheng, Yunchao Fan, Lei Gao, Zichen Huang, Bodong Chen, Miaolang Long","doi":"10.1080/15391523.2024.2304066","DOIUrl":"https://doi.org/10.1080/15391523.2024.2304066","url":null,"abstract":"As an effective form of pedagogy, online collaborative learning has received increasing application in the field of education. However, learners often feel frustrated with regard to knowledge build...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"392 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-22DOI: 10.1080/15391523.2024.2303025
Kirk Vanacore, Erin Ottmar, Allison Liu, Adam Sales
The impact of educational programs on student learning is contingent upon the quality and fidelity of their implementations. Yet, the most reliable method of implementation monitoring, direct obser...
{"title":"Remote monitoring of implementation fidelity using log-file data from multiple online learning platforms","authors":"Kirk Vanacore, Erin Ottmar, Allison Liu, Adam Sales","doi":"10.1080/15391523.2024.2303025","DOIUrl":"https://doi.org/10.1080/15391523.2024.2303025","url":null,"abstract":"The impact of educational programs on student learning is contingent upon the quality and fidelity of their implementations. Yet, the most reliable method of implementation monitoring, direct obser...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"123 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139579311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.1080/15391523.2024.2303010
Mary H. Moen
{"title":"Effective leader practices to leverage school librarians as leaders in one-to-one computing","authors":"Mary H. Moen","doi":"10.1080/15391523.2024.2303010","DOIUrl":"https://doi.org/10.1080/15391523.2024.2303010","url":null,"abstract":"","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"4 12","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139438472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.1080/15391523.2023.2298889
S. Wininger, D. E. Lancaster, J. L. Redifer, W. P. Derryberry
{"title":"K-12 teachers’ beliefs about and reactions to students’ off-task technology use","authors":"S. Wininger, D. E. Lancaster, J. L. Redifer, W. P. Derryberry","doi":"10.1080/15391523.2023.2298889","DOIUrl":"https://doi.org/10.1080/15391523.2023.2298889","url":null,"abstract":"","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"53 8","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.1080/15391523.2023.2266518
Christine Wusylko, Lauren Weisberg, Raymond A. Opoku, Brian Abramowitz, Jessica Williams, Wanli Xing, Teresa Vu, Michelle Vu
Abstract Social media has the unique capacity to expose many learners to media literacy instruction via targeted campaigns. Investigating learner engagement and reaction to these efforts may be a fruitful endeavor for researchers that can inform the design of future campaigns. However, the massive datasets associated with social media posts are difficult, and often impossible, to analyze with traditional qualitative methods. This study seeks to address this problem by leveraging machine learning techniques to collect and analyze Big Data from two different media literacy campaigns on the youth-oriented social media platform TikTok. Specifically, we explore the ways topic modeling, sentiment analysis, and network analysis can provide insight into learner engagement with these campaigns and discuss limitations and implications for stakeholders interested in utilizing these approaches.
{"title":"Using machine learning techniques to investigate learner engagement with TikTok media literacy campaigns","authors":"Christine Wusylko, Lauren Weisberg, Raymond A. Opoku, Brian Abramowitz, Jessica Williams, Wanli Xing, Teresa Vu, Michelle Vu","doi":"10.1080/15391523.2023.2266518","DOIUrl":"https://doi.org/10.1080/15391523.2023.2266518","url":null,"abstract":"Abstract Social media has the unique capacity to expose many learners to media literacy instruction via targeted campaigns. Investigating learner engagement and reaction to these efforts may be a fruitful endeavor for researchers that can inform the design of future campaigns. However, the massive datasets associated with social media posts are difficult, and often impossible, to analyze with traditional qualitative methods. This study seeks to address this problem by leveraging machine learning techniques to collect and analyze Big Data from two different media literacy campaigns on the youth-oriented social media platform TikTok. Specifically, we explore the ways topic modeling, sentiment analysis, and network analysis can provide insight into learner engagement with these campaigns and discuss limitations and implications for stakeholders interested in utilizing these approaches.","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"29 3","pages":"72 - 93"},"PeriodicalIF":5.1,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139452180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.1080/15391523.2023.2280385
Sarah McGrew, Angela M. Kohnen
Misinformation has been created and spread for centuries, but the Internet facilitates easy, rapid creation and dissemination of misleading or false information in ways that we are still understanding and adjusting to. Digital misinformation reaches into many realms, from entertainment to health to politics. Without adequate defenses in place, misinformation can—and likely does— affect consequential decisions like whether to be vaccinated or who to vote for. Given the scale of these threats, a wide range of responses are necessary, including platform reforms, policy changes, and educational efforts. We are broadly focused on educational efforts, or efforts to slow both the supply of and the demand for misinformation by supporting people to recognize, evaluate, and refrain from sharing misinformation. Efforts in this area vary widely in their scope and approach. For example, some projects attempt to inoculate users against common misinfor-mation tactics like using emotional language and discrediting opponents (e.g. Roozenbeek et al., 2022). Others embed short messages in social media platforms to remind users to verify sources and claims (e.g. Panizza et al., 2022). Yet another approach focuses on labeling or debunking misinformation as it surfaces on platforms, either by attaching fact checks to articles with questionable claims (e.g. Clayton et al., 2020; Pennycook et al., 2020) or by circulating new posts that directly address common claims made by misinformation (e.g. about COVID-19; Vraga & Bode, 2021). All of these efforts have shown promise in tackling misinformation and reaching wide audiences. However, these are mostly quick, lightweight interventions that may struggle to fundamentally shift people’s approaches to evaluating digital information. In this special issue, we focus on efforts to cultivate online information literacy, or the knowledge, skills,
{"title":"Tackling misinformation through online information literacy: Structural and contextual considerations","authors":"Sarah McGrew, Angela M. Kohnen","doi":"10.1080/15391523.2023.2280385","DOIUrl":"https://doi.org/10.1080/15391523.2023.2280385","url":null,"abstract":"Misinformation has been created and spread for centuries, but the Internet facilitates easy, rapid creation and dissemination of misleading or false information in ways that we are still understanding and adjusting to. Digital misinformation reaches into many realms, from entertainment to health to politics. Without adequate defenses in place, misinformation can—and likely does— affect consequential decisions like whether to be vaccinated or who to vote for. Given the scale of these threats, a wide range of responses are necessary, including platform reforms, policy changes, and educational efforts. We are broadly focused on educational efforts, or efforts to slow both the supply of and the demand for misinformation by supporting people to recognize, evaluate, and refrain from sharing misinformation. Efforts in this area vary widely in their scope and approach. For example, some projects attempt to inoculate users against common misinfor-mation tactics like using emotional language and discrediting opponents (e.g. Roozenbeek et al., 2022). Others embed short messages in social media platforms to remind users to verify sources and claims (e.g. Panizza et al., 2022). Yet another approach focuses on labeling or debunking misinformation as it surfaces on platforms, either by attaching fact checks to articles with questionable claims (e.g. Clayton et al., 2020; Pennycook et al., 2020) or by circulating new posts that directly address common claims made by misinformation (e.g. about COVID-19; Vraga & Bode, 2021). All of these efforts have shown promise in tackling misinformation and reaching wide audiences. However, these are mostly quick, lightweight interventions that may struggle to fundamentally shift people’s approaches to evaluating digital information. In this special issue, we focus on efforts to cultivate online information literacy, or the knowledge, skills,","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"139 25","pages":"1 - 6"},"PeriodicalIF":5.1,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139452970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-15DOI: 10.1080/15391523.2023.2287246
Tsui-Yuan Chang, Gwo-Jen Hwang, Yun-Fang Tu
With its increasing popularity, understanding learners’ perceptions of online education has become more important. The present study employed drawing analysis to examine university students’ concep...
{"title":"From realistic to idealistic online learning: a drawing analysis of the conceptions of university students with different self-regulation levels","authors":"Tsui-Yuan Chang, Gwo-Jen Hwang, Yun-Fang Tu","doi":"10.1080/15391523.2023.2287246","DOIUrl":"https://doi.org/10.1080/15391523.2023.2287246","url":null,"abstract":"With its increasing popularity, understanding learners’ perceptions of online education has become more important. The present study employed drawing analysis to examine university students’ concep...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"32 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138687188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1080/15391523.2023.2266060
Zixi Chen, Kaitlin T. Torphy Knake, Hamid Karimi, Nicole Donzella
The emerging big data allows educational studies to examine teaching and learning behaviors over time and at scale. Less available is population-representative big data. This paper builds the first...
{"title":"Building a nationally representative sample of teachers’ online and offline: the Public Instructional Network of School Resources","authors":"Zixi Chen, Kaitlin T. Torphy Knake, Hamid Karimi, Nicole Donzella","doi":"10.1080/15391523.2023.2266060","DOIUrl":"https://doi.org/10.1080/15391523.2023.2266060","url":null,"abstract":"The emerging big data allows educational studies to examine teaching and learning behaviors over time and at scale. Less available is population-representative big data. This paper builds the first...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"47 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138575491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1080/15391523.2023.2288912
Mehdi Darban
The paper examines the impact of artificial intelligence (AI) in unexplored context of virtual project-based team learning. We built on relevant research developed a framework grounded in shared me...
{"title":"The future of virtual team learning: navigating the intersection of AI and education","authors":"Mehdi Darban","doi":"10.1080/15391523.2023.2288912","DOIUrl":"https://doi.org/10.1080/15391523.2023.2288912","url":null,"abstract":"The paper examines the impact of artificial intelligence (AI) in unexplored context of virtual project-based team learning. We built on relevant research developed a framework grounded in shared me...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"175 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138687225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1080/15391523.2023.2288233
Robert O. Davis, Yong Jik Lee, Joseph Vincent, Sunok Lee, Daeun Kim, Jongho Kim
Early research on pedagogical agents centered on functionality within multimedia environments. A specific, yet under-researched area was the contextual relevance of the agent’s appearance, leaving ...
{"title":"Revisiting contextual relevance: pedagogical agent appearance","authors":"Robert O. Davis, Yong Jik Lee, Joseph Vincent, Sunok Lee, Daeun Kim, Jongho Kim","doi":"10.1080/15391523.2023.2288233","DOIUrl":"https://doi.org/10.1080/15391523.2023.2288233","url":null,"abstract":"Early research on pedagogical agents centered on functionality within multimedia environments. A specific, yet under-researched area was the contextual relevance of the agent’s appearance, leaving ...","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"286 3","pages":""},"PeriodicalIF":5.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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