Computers and Education Open最新文献

{"title":"Evaluating the content structure of intelligent tutor systems—A psychological network analysis","authors":"Markus W.H. Spitzer ,&nbsp;Lisa Bardach ,&nbsp;Younes Strittmatter ,&nbsp;Jennifer Meyer ,&nbsp;Korbinian Moeller","doi":"10.1016/j.caeo.2024.100198","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100198","url":null,"abstract":"<div><p>The adoption of intelligent tutoring systems (ITSs) worldwide has led to a considerable accumulation of process data as students interact with different learning topics within these systems. Typically, these learning topics are structured within ITSs (e.g., the fraction topic includes subtopics such as a fraction number line subtopic). However, there is a lack of methods that offer quick, data-driven insights into the content structure of ITSs, particularly through easily accessible visualizations. Here, we applied psychological network analysis to process data (230,241 students; 5,365,932 problem sets) from an ITS for learning mathematics to explore performance interdependencies between 40 different subtopics. We argue that the visualization of these content interdependencies allows for a quick empirical evaluation of the validity of the existing structuring of the respective learning content. These insights allow for deriving recommendations concerning potential changes in the ITS structure and are thus highly valuable for ITS developers. Our results are also relevant for researchers as the interdependencies illustrated through psychological network analysis can contribute towards a better understanding of the interplay between mathematical skills. Together, our results indicate that psychological network analysis represents a valuable data-driven method to evaluate and optimize ITSs.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"7 ","pages":"Article 100198"},"PeriodicalIF":4.1,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000387/pdfft?md5=42fa45d70865909aecd605c7ab46ce98&pid=1-s2.0-S2666557324000387-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141433928","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}

{"title":"The datafication of student information on X (Twitter)","authors":"Cody Pritchard ,&nbsp;Conrad Borchers ,&nbsp;Joshua, M. Rosenberg ,&nbsp;Alexa K. Fox ,&nbsp;Sondra M. Stegenga","doi":"10.1016/j.caeo.2024.100197","DOIUrl":"10.1016/j.caeo.2024.100197","url":null,"abstract":"<div><p>The sharing of personally identifiable information (PII) through social media platforms poses known risks to children's online privacy and safety. While the risks of oversharing PII through a range of digital contexts are becoming better understood, limited research has documented the social media practices of educational institutions that have a fiduciary responsibility to children. This study seeks to understand the role of educational institutions in putting students’ privacy at risk by investigating their social media practices on X (formerly Twitter). This paper extends previous research (Rosenberg et al., 2022a) by exploring how often students' PII (e.g., names, images, and phone numbers) and other social identities (e.g., gender identity, religion, race, and ethnicity) are exposed on X. Additionally, we examine both images and <em>videos</em> of posts shared by educational institutions. Using a data set of approximately 20.6 million posts made by K-12 education institutions in the United States, we explore the extent to which students’ PII is shared with the public on X. Our analyses suggest that approximately 4 % of posts that contain images and videos (approximately 800,000 posts in the overall data set) included an identifiable face of a student or students along with their name(s) and 2.3 % ascribed students’ gender identity. Given the extent of disclosed PII and the potential privacy risks, this study provides additional insight for educational stakeholders to cultivate safer social media practices, seeking to mitigate potential risks to students' privacy and improve students’ digital rights.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"7 ","pages":"Article 100197"},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000375/pdfft?md5=3fd8bc71057540d938e75ec0c32f11d2&pid=1-s2.0-S2666557324000375-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141405000","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}

{"title":"The Googlization of the classroom: Is the UK effective in protecting children's data and rights?","authors":"","doi":"10.1016/j.caeo.2024.100195","DOIUrl":"10.1016/j.caeo.2024.100195","url":null,"abstract":"<div><p>There has been an explosion in uses of educational technology (EdTech) to support schools’ teaching, learning, assessment and administration. This article asks whether UK EdTech and data protection policies protect children's rights at school. It adopts a children's rights framework to explore how EdTech impacts children's rights to education, privacy and freedom from economic exploitation, taking Google Classroom as a case study. The research methods integrate legal research, interviews with UK data protection experts and education professionals working at various levels from national to local, and a socio-technical investigation of the flow of children's data through Google Classroom. The findings show that Google Classroom undermines children's privacy and data protection, potentially infringing children's other rights. However, they also show that regulation has impacted on Google's policy and practice. Specifically, we trace how various governments’ deployment of a range of legal arguments has enabled them to regulate Google's relationship with schools to improve its treatment of children's data. Although the UK government has not brought such actions, the data flow investigation shows that Google has also improved its protection of children's data in UK schools as a result of these international actions. Nonetheless, multiple problems remain, due both to Google's non-compliance with data protection regulations and schools’ practices of using Google Classroom. We conclude with a blueprint for the rights-respecting treatment of children's education data that identifies needed actions for the UK Department for Education, data protection authority, and industry, to mitigate against harmful practices and better support schools.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"7 ","pages":"Article 100195"},"PeriodicalIF":4.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000351/pdfft?md5=d6e31f193ffc4e4c432e57f8c197921f&pid=1-s2.0-S2666557324000351-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277721","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}

{"title":"Connectedness with students as a key factor in online teaching self-efficacy","authors":"Rosa K. Leino ,&nbsp;Tomas Kaqinari ,&nbsp;Elena Makarova ,&nbsp;Anna K. Döring","doi":"10.1016/j.caeo.2024.100192","DOIUrl":"10.1016/j.caeo.2024.100192","url":null,"abstract":"<div><p>This paper investigates how lecturers’ connectedness with students affected their experience of online teaching during the first COVID-19 lockdown in the UK and Switzerland. We examined how this connectedness predicted lecturers’ self-efficacy in online teaching. This was in addition to other social context variables (connectedness with colleagues and perceived support from the university) and their previous experience with digital tools. The shift to online teaching in the lockdown period abruptly removed any in-person contact between lecturers and their students. Lecturers’ self-efficacy in online teaching is crucial to student motivation, achievement, and the lecturer's own teaching experience. Likewise, lecturers’ connectedness with students and colleagues has been identified as a key factor in learning. Consequently, this study explored how different forms of connectedness predicted lecturers’ self-efficacy in the new teaching environment. A total of 252 lecturers from UK and Swiss universities completed an online survey about their teaching experiences before and during the COVID-19 lockdown. Multiple regressions were used to predict lecturers’ online teaching self-efficacy. The results revealed that connectedness with students was a significant and positive predictor of online teaching self-efficacy. However, connectedness with colleagues and perceived support from the university did not. The perception that digital tools enhanced teaching prior to the lockdown was a significant predictor only for the UK lecturers, but not for the Swiss ones. These findings point towards lecturers’ connectedness with their students being a pathway to success in online teaching.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100192"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000326/pdfft?md5=35ca8ad17e5e25ed0ae4eb36da57e98b&pid=1-s2.0-S2666557324000326-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141138490","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}

{"title":"Assessing the privacy of digital products in Australian schools: Protecting the digital rights of children and young people","authors":"Luci Pangrazio ,&nbsp;Anna Bunn","doi":"10.1016/j.caeo.2024.100187","DOIUrl":"10.1016/j.caeo.2024.100187","url":null,"abstract":"<div><p>The increasing reliance in schools on educational technology (edtech) poses a threat to children's digital privacy, particularly where children's data is used for or shared with others for commercial purposes. However, assessing the privacy of digital products is challenging given the opaque and evolving nature of the digital economy. Many schools share the responsibility for assessing edtech with education departments and authorities; however, to date, there has been very little empirical or theoretical work on how schools, education departments and authorities evaluate the privacy risks and data practices associated with the digital products used in schools. Drawing on an analysis of the Safer Technologies 4 Schools (ST4S) framework developed by Education Services Australia, education department policies, as well as interviews with education department staff and representatives, we examine how the data practices of digital products are examined in government schools in Australia and how schools are supported to choose tools that demonstrate best practice in terms of protecting students’ digital privacy. Findings suggest that while the goal of the ST4S framework is to streamline and unify digital privacy standards across states and territories, the complexity of the Australian education system, the number and diversity of digital products used, and the different governance approaches across the country make this difficult. Our conclusions reveal a compliance culture towards children's digital privacy, rather than a best practice approach, and a trust (or even ‘overtrust’) in ‘big tech’. However, we note some promising developments in this area and make recommendations for future research.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000272/pdfft?md5=786dffd402a18b8e3c0205b9a53e595c&pid=1-s2.0-S2666557324000272-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141030005","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}

{"title":"AI in education: Comparative perspectives from STEM and Non-STEM instructors","authors":"Muhammed Parviz","doi":"10.1016/j.caeo.2024.100190","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100190","url":null,"abstract":"<div><p>The integration of artificial intelligence into education has emerged as a promising avenue for enriching teaching and learning experiences. Nevertheless, the successful implementation of artificial intelligence in educational contexts hinges upon various factors, one of which is the perspective of instructors. With this in mind, this study aimed to examine the perspectives of 536 instructors in STEM and non-STEM disciplines regarding AI integration. The respondents’ thoughts, opinions, and concerns regarding advantages, disadvantages and challenges were gathered through an online questionnaire featuring both closed and open-ended questions. Additionally, a series of semi-structured interview sessions were conducted with a cohort of instructors to collect qualitative and quantitative data. The findings revealed that both STEM and non-STEM instructors expressed positive attitudes toward the integration of AI technologies into education. However, notable differences in responses and concerns were also identified in relation to the perceived capabilities and limitations of AI technologies within educational contexts. The results further elucidated a spectrum of opinions on the benefits (e.g., scalability and tirelessness), drawbacks (e.g., deepfake technology and comfort-seeking behavior), and potential challenges (e.g., educational disillusionment and espionage) associated with AI integration. The study concluded by discussing the implications of these findings for STEM and non-STEM education and offering recommendations for the effective and ethical integration of AI technologies in classrooms.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000302/pdfft?md5=5fe17317b8eb33be357394e46f6ddd26&pid=1-s2.0-S2666557324000302-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141163676","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}

{"title":"Academic dishonesty out, use of resources in","authors":"Shahin Vaezi ,&nbsp;Mahdi Vaezi ,&nbsp;Fatemeh Nami","doi":"10.1016/j.caeo.2024.100193","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100193","url":null,"abstract":"<div><p>The outbreak of COVID-19 necessitated the call for integrating teaching and assessment into virtual environments. To explore the types of resources students accessed during online exams, engineering students were administered an unproctored online English for Academic Purposes (EAP) mid-term exam. Subsequently, a questionnaire was administered to investigate students’ use of resources while taking the exam. The results of an exploratory factor analysis was used to categorize students’ use of resources, external to one's self, shedding light on student perception of the act. The analysis revealed that 60 % of the common variance could be attributed to access to both human and nonhuman resources external to oneself. The transition from face to face teaching and assessment to online education has led to an increase in the utilization of resources external to one's self. Traditionally this act has been termed academic dishonesty. The study argues that this should not be viewed as a disruption, but rather a symptom of the transition embraced by online education with recourse to high accessibility to online and offline resources. Despite the general notion that of the use of resources external to one's self is discouraged, students exhibited a prevalent tendency to use resources external to themselves on the online exam. Of significance is the call for a redefinition of what constitutes academic misbehavior or dishonesty in a world that is digitally connected 24/7.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000338/pdfft?md5=fbfc7d40aed2c79aeb769b04a917c175&pid=1-s2.0-S2666557324000338-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141090826","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}

{"title":"Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources","authors":"Rethabile Rosemary Molefi ,&nbsp;Musa Adekunle Ayanwale ,&nbsp;Lehlohonolo Kurata ,&nbsp;Julia Chere-Masopha","doi":"10.1016/j.caeo.2024.100191","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100191","url":null,"abstract":"<div><p>This study investigates the acceptance and utilization of artificial intelligence (AI) among in-service teachers in Lesotho, focusing on the mediating role of school support and resources (SSR). In Lesotho's educational landscape, which is characterized by a growing interest in technology integration, this study fills an essential gap in the existing literature by exploring in-service teachers' perspectives on AI adoption and the mediating influence of SSR. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, the study adopts a cross-sectional design, collecting data from a sample of 315 in-service teachers through online surveys. The data was analyzed using maximum likelihood estimation. The results reveal a substantial positive relationship between perceived usefulness, perceived ease of use, and a positive attitude towards AI, with SSR playing a pivotal role as a complementary mediator in these connections. However, the study identifies a non-significant relationship between technical proficiency and behavioral intention, suggesting a need for further investigation into the technical skills essential for effective AI integration. The results highlight the critical role of SSR in shaping in-service teachers' intentions to use AI in their teaching practices. As a result, the study recommends tailored continuous professional development programs and collaborative learning communities to enhance teachers' skills. Additionally, it emphasizes the importance of advocating for policies that support AI integration in education and underscores the ethical considerations related to AI use. We discuss the implications of our results concerning integrating AI into teachers' teaching practices in schools and outline future directions.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100191"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000314/pdfft?md5=62c14341849dca393a9424b237c1a587&pid=1-s2.0-S2666557324000314-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141083300","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}

{"title":"A Latent Dirichlet Allocation approach to understanding students’ perceptions of Automated Writing Evaluation","authors":"Joshua Wilson ,&nbsp;Saimou Zhang ,&nbsp;Corey Palermo ,&nbsp;Tania Cruz Cordero ,&nbsp;Fan Zhang ,&nbsp;Matthew C. Myers ,&nbsp;Andrew Potter ,&nbsp;Halley Eacker ,&nbsp;Jessica Coles","doi":"10.1016/j.caeo.2024.100194","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100194","url":null,"abstract":"<div><p>Automated writing evaluation (AWE) has shown promise in enhancing students’ writing outcomes. However, further research is needed to understand how AWE is perceived by middle school students in the United States, as they have received less attention in this field. This study investigated U.S. middle school students’ perceptions of the <em>MI Write</em> AWE system. Students reported their perceptions of MI Write's usefulness using Likert-scale items and an open-ended survey question. We used Latent Dirichlet Allocation (LDA) to identify latent topics in students’ comments, followed by qualitative analysis to interpret the themes related to those topics. We then examined whether these themes differed among students who agreed or disagreed that MI Write was a useful learning tool. The LDA analysis revealed four latent topics: (1) students desire more in-depth feedback, (2) students desire an enhanced user experience, (3) students value MI Write as a learning tool but desire greater personalization, and (4) students desire increased fairness in automated scoring. The distribution of these topics varied based on students’ ratings of MI Write's usefulness, with Topic 1 more prevalent among students who generally did not find MI Write useful and Topic 3 more prominent among those who found MI Write useful. Our findings contribute to the enhancement and implementation of AWE systems, guide future AWE technology development, and highlight the efficacy of LDA in uncovering latent topics and patterns within textual data to explore students’ perspectives of AWE.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100194"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266655732400034X/pdfft?md5=59757519cdab584f256a934357fa2a53&pid=1-s2.0-S266655732400034X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141090827","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}

{"title":"The datafication of student engagement and children's digital rights","authors":"Chris Zomer","doi":"10.1016/j.caeo.2024.100189","DOIUrl":"https://doi.org/10.1016/j.caeo.2024.100189","url":null,"abstract":"<div><p>In this commentary paper, I will introduce the concept of engagement data. I define engagement data as the digital metrics, calculations and visualisations that are deemed to give an insight into students’ on-task behaviour, their participation, their perceived capacity to pay attention, or their (technical) interactions with an educational platform. These kinds of data are common in Learning Management Systems and learning content platforms on which schools increasingly rely. The categories of engagement data discussed in this paper include time spent on-task, task completion, contribution, and biometric data. Besides conceptualising engagement data, this paper invites both scholars and educators to reflect critically on the datafication of engagement. I will argue that engagement data only offer a limited, quantified idea of student engagement and that this has far-reaching implications for children's digital rights. Children's behavioural data is harvested without their explicit consent or knowledge. These engagement data then become prescriptive constructs used for monitoring and accountability purposes, ignoring children's voice in relation to their own (dis)engagement.</p></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"6 ","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666557324000296/pdfft?md5=b1020a5f3ead2236396f273ff27f4f35&pid=1-s2.0-S2666557324000296-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141073150","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}