Xinli Zhang , Yuchen Chen , Lailin Hu , Yiwei Bao , Yun-Fang Tu , Gwo-Jen Hwang
{"title":"A metaphor-based robot programming approach to facilitating young children’s computational thinking and positive learning behaviors","authors":"Xinli Zhang , Yuchen Chen , Lailin Hu , Yiwei Bao , Yun-Fang Tu , Gwo-Jen Hwang","doi":"10.1016/j.compedu.2024.105039","DOIUrl":"10.1016/j.compedu.2024.105039","url":null,"abstract":"<div><p>In the artificial intelligence age, cultivating young children's computational thinking (CT) has sparked tremendous attention. Programmable robotics is a developmental-appropriate and screen-free means that provides young children with great opportunities to learn programming and develop CT. However, it is reported that young children might have difficulties learning abstract CT concepts. As a helpful pedagogical facilitator, metaphors can help turn abstract concepts into more concrete and clear concepts that learners are familiar with. Therefore, this research proposed a metaphor-based robot programming (MRP) approach and explored its impact on young children's CT and behavioral patterns. A total of 118 children aged 5–6 were recruited in this experiment with two conditions: the experimental group adopted the metaphor-based robot programming (MRP) approach while the control group used the conventional robot programming (CRP) approach. Results revealed that children who adopted the MRP approach outperformed children who adopted the CRP approach on CT. In addition, behavioral analysis indicated that the proposed MRP approach could facilitate children's superior learning performance and more positive learning behaviors, so as to help them achieve learning objectives. Accordingly, this study can provide insightful guidance and inspiration for future research on effective programming teaching and CT development for young children.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"215 ","pages":"Article 105039"},"PeriodicalIF":12.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140268980","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}
Slaviša Radović, Niels Seidel, Dennis Menze, Regina Kasakowskij
{"title":"Investigating the effects of different levels of students' regulation support on learning process and outcome: In search of the optimal level of support for self-regulated learning","authors":"Slaviša Radović, Niels Seidel, Dennis Menze, Regina Kasakowskij","doi":"10.1016/j.compedu.2024.105041","DOIUrl":"10.1016/j.compedu.2024.105041","url":null,"abstract":"<div><p>Students in higher education who actively manage and control their own learning processes have better learning outcomes, more efficient learning progress, and other non-academic benefits than those who do not. However, students often have poor self-regulation practices, lack reflective thinking, and fail to monitor their learning against defined goals. Therefore, a variety of advanced learning technologies and features have been developed to support students with regulation. Nevertheless, the optimal level of regulation support and the most effective combination of these features remain unestablished in the existing research literature. Therefore, this study employs quantitative research to examine the effectiveness of two learning environments with different levels of self-regulation support (less and more) on students' learning academic outcomes, learning process, and satisfaction. Both variants combine the elements of learning dashboards, goal-setting activity, self-assessment task, reflection support, and personal recommendation, with differences in the level of supporting students' regulation. Our findings reveal that students who received higher levels of self-regulation support tended to be more active readers and visited online learning materials and course overviews more frequently. While they outperformed students in the control group, it's noteworthy that these students did not necessarily outperform their peers who received less support, particularly in the context of self-assessment tasks. This study has also highlighted the need for further research in this area (e.g., self-assessment accuracy), including the development of an instrument that can objectively measure and evaluate the level of self-regulated learning support.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"215 ","pages":"Article 105041"},"PeriodicalIF":12.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0360131524000551/pdfft?md5=eebf2aacd757f84492858d8667ce0326&pid=1-s2.0-S0360131524000551-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140173333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marek Urban , Filip Děchtěrenko , Jiří Lukavský , Veronika Hrabalová , Filip Svacha , Cyril Brom , Kamila Urban
{"title":"ChatGPT improves creative problem-solving performance in university students: An experimental study","authors":"Marek Urban , Filip Děchtěrenko , Jiří Lukavský , Veronika Hrabalová , Filip Svacha , Cyril Brom , Kamila Urban","doi":"10.1016/j.compedu.2024.105031","DOIUrl":"10.1016/j.compedu.2024.105031","url":null,"abstract":"<div><p>University students often employ generative artificial intelligence tools such as ChatGPT in resolution of ill-defined problem-solving tasks. However, the experimental evidence about effects of ChatGPT on complex problem-solving performance is still missing. In this preregistered experiment, the impact of ChatGPT on performance in a complex creative problem-solving task was investigated in 77 university students solving a task with ChatGPT in comparison to 68 students solving a task without it. ChatGPT use significantly improved self-efficacy for task resolution (<em>d</em> = 0.65) and enhanced the quality (<em>d</em> = 0.69), elaboration (<em>d</em> = 0.61), and originality (<em>d</em> = 0.55) of solutions. Moreover, participants with ChatGPT assistance perceived task as easier (<em>d</em> = 0.56) and requiring less mental effort (<em>d</em> = 0.58). However, use of ChatGPT did not make task resolution more interesting (<em>d</em> = 0.08), and the impact of ChatGPT on metacognitive monitoring accuracy was unclear. Although there were no significant differences in absolute accuracy between students solving the task with and without the assistance of ChatGPT, the absence of correlation between self-evaluation judgments and performance suggests that participants struggled to calibrate their self-evaluations when using ChatGPT. Notably, the perceived usefulness of ChatGPT appeared to inform self-evaluation judgments, resulting in higher inaccuracy. The implications for hybrid human-AI regulation (HHAIR) theory are discussed. To regulate effectively, students using AI tools should focus on valid metacognitive cues instead of the perceived ease of ChatGPT-assisted problem-solving.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"215 ","pages":"Article 105031"},"PeriodicalIF":12.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140173388","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}
Armin Fabian , Tim Fütterer , Iris Backfisch , Erika Lunowa , Walther Paravicini , Nicolas Hübner , Andreas Lachner
{"title":"Unraveling TPACK: Investigating the inherent structure of TPACK from a subject-specific angle using test-based instruments","authors":"Armin Fabian , Tim Fütterer , Iris Backfisch , Erika Lunowa , Walther Paravicini , Nicolas Hübner , Andreas Lachner","doi":"10.1016/j.compedu.2024.105040","DOIUrl":"10.1016/j.compedu.2024.105040","url":null,"abstract":"<div><p>Against the backdrop of digitalization, it is imperative to provide pre-service teachers with adequate training opportunities to foster their professional knowledge regarding technology integration in teaching-learning scenarios. However, to date, only limited insights into the empirical nature of such knowledge – often subsumed under the term Technological Pedagogical and Content Knowledge (i.e., TPCK) – are possible given the heterogeneity of prior research investigating the empirical relationship between different knowledge components. This heterogeneity is likely due to the predominant use of self-reports in previous studies. Against this background, the present study pursued two goals. The first goal was to investigate the empirical nature of TPCK among pre-service teachers, utilizing test-based instruments to explore TPCK's nature from a subject-specific angle, that is, its relationship with Pedagogical Content Knowledge (PCK) and Technological Knowledge (TK). Given the widespread use of self-reports, the study's second goal was to examine the relationship between test-based and self-reported TPCK, exploring possible associated factors (e.g., pre-service teachers' gender, prior experience in teaching with technologies in school, or metacognitive accuracy) that may explain why both measures are linked only weakly. Findings reveal that both PCK and TK statistically predicted TPCK to a similar extent highlighting the integrated nature of TPCK. The relationship between test-based and self-reported TPCK was moderated by pre-service teachers' metacognitive accuracy, but not by their gender or prior experience. Together, these insights offer valuable guidance for refining teacher training regarding effective technology integration by indicating the need to target not only PCK and TK but also TPCK.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"217 ","pages":"Article 105040"},"PeriodicalIF":12.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140173344","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}
{"title":"Aligning open educational resources to new taxonomies: How AI technologies can help and in which scenarios","authors":"Zhi Li , Zachary A. Pardos , Cheng Ren","doi":"10.1016/j.compedu.2024.105027","DOIUrl":"10.1016/j.compedu.2024.105027","url":null,"abstract":"<div><p>Aligning open educational resources (OER) to skill taxonomies is a common task in the education field and helps teachers better locate material that aligns with the standards of their curriculum. When taxonomies change, as they periodically do, re-tagging the increasing mass of open educational resources is needed. The process of manual tagging is, however, exceedingly labor intensive. We propose and evaluate a novel combination of machine learning methods to help automate tagging open educational resources with skills from an existing taxonomy as well as skills from any newly introduced taxonomy. We collected text, image figures, and videos from tens of thousands of educational resources from two major digital learning platforms to answer the research questions of: how effective are machine learning models in automatically updating OER classification to reflect a new taxonomy (RQ1), and which models may be of practical use in different scenarios (RQ2)? Using several taxonomies, including the US Common Core, we find that while full automation is not practically viable, our most generalizable model can reach non-expert human labeling performance requiring only 100 labeled examples and near expert level with 5000. We believe these novel findings may have immediate utility for practitioners and policymakers and better ready the growing landscape of open educational resources for the advent of new taxonomies ahead. We publicly release our pre-trained US Common Core and new taxonomy tagging models, providing guidance on their viability in various real-world scenarios.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"216 ","pages":"Article 105027"},"PeriodicalIF":12.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140173339","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}
{"title":"Academic procrastination, incentivized and self-selected spaced practice, and quiz performance in an online programming problem system: An intensive longitudinal investigation","authors":"Yingbin Zhang , Luc Paquette , Xiaoyong Hu","doi":"10.1016/j.compedu.2024.105029","DOIUrl":"https://doi.org/10.1016/j.compedu.2024.105029","url":null,"abstract":"<div><p>Time management is crucial for college students' academic success and learning of computer programming. Yet the changes of time management behaviors and their associations with learning outcomes are underexplored in online learning of programming. To address the gap, this study employed an intensive longitudinal approach to examine undergraduates’ time management behaviors in an online programming problem system. Specifically, we analyzed weekly indicators of academic procrastination and spaced practice derived from programming traces. We applied dynamic structural equation modeling to examine the changes in these behaviors over time and their correlations with weekly quiz performance. Academic procrastination and self-selected spaced practice showed a significant upward trend over time, while incentivized spaced practice exhibited a significant downward trend. Moreover, students with prior programming experience showed a greater growth rate in spacing behaviors. At both within- and between-person levels, procrastination predicted quiz performance significantly and negatively, while self-selected spaced practice predicted quiz performance significantly and positively. In contrast, incentivized spaced practice predicted quiz performance positively at the within-person level but negatively at the between-person level. Additionally, quiz performance in the current week predicted subsequent time management behaviors significantly. These findings contribute to the understanding of procrastination and spaced practice in online programming learning and have implications for the design of scaffolding on time management. Furthermore, this study demonstrates the significance of combining intensive longitudinal approaches and action logs in examining the temporality of learning in online environments.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"214 ","pages":"Article 105029"},"PeriodicalIF":12.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140066729","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}
Marvin Roski , Ratan Sebastian , Ralph Ewerth , Anett Hoppe , Andreas Nehring
{"title":"Learning analytics and the Universal Design for Learning (UDL): A clustering approach","authors":"Marvin Roski , Ratan Sebastian , Ralph Ewerth , Anett Hoppe , Andreas Nehring","doi":"10.1016/j.compedu.2024.105028","DOIUrl":"https://doi.org/10.1016/j.compedu.2024.105028","url":null,"abstract":"<div><p>In the context of inclusive education, Universal Design for Learning (UDL) is a framework used worldwide to create learning opportunities accessible to all learners. While much research focused on the design and students' perceptions of UDL-based learning settings, studies on students’ usage patterns in UDL-guided elements, particularly in digital environments, are still scarce. Therefore, we analyze and cluster the usage patterns of 9th and 10th graders in a web-based learning platform called I<sub>3</sub>Learn.</p><p>The platform focuses on chemistry learning, and UDL principles guide its design. We collected the temporal usage patterns of UDL-guided elements of 384 learners in detailed log files. The collected data includes the time spent using video and/or text as a source of information, working on learning tasks with or without help and working on self-assessments. We used Exploratory Factor Analysis (EFA) to identify relevant factors in the observed usage behaviors. Based on the factor loadings, we extracted features for k-means clustering and named the resulting groups based on their usage patterns and learner characteristics. The EFA revealed four factors suggesting that learners remain consistent in selecting UDL-guided elements that require a decision (video or text, tasks with or without help). Based on these four factors, the cluster analysis identifies six different groups. We discuss these results as a starting point to provide individualized learning support through further artificial intelligence applications and inform educators about learner activity through a dashboard.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"214 ","pages":"Article 105028"},"PeriodicalIF":12.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0360131524000423/pdfft?md5=48a50f4b0bc1a2e8d74151895e680ef0&pid=1-s2.0-S0360131524000423-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140041372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The impact of school support for professional development on teachers' adoption of student-centered pedagogy, students’ cognitive learning and abilities: A three-level analysis","authors":"Siu-Cheung Kong , Yi-Qing Wang","doi":"10.1016/j.compedu.2024.105016","DOIUrl":"10.1016/j.compedu.2024.105016","url":null,"abstract":"<div><p>Student-centered pedagogy (SCP) is highly considered for its potential to facilitate cognitive learning in Computational Thinking (CT) education. However, there is a noticeable gap in understanding its influence on students' cognitive development from a multilevel perspective. This study delves into cognitive learning theories and aims to bridge the existing gap by introducing a three-level conceptual model to illustrate how the influence of SCP on students' cognitive CT abilities is mediated through the cognitive learning processes. This multilevel approach simultaneously explores SCP within the intricate school environment where factors at the school, teacher, and student levels are closely intertwined. Data was collected from 82 programming teachers and their 2433 students across 43 Hong Kong primary schools. Using multilevel modeling, results indicate that the adoption of SCP is significantly anchored by school support on teacher professional development (TPD), which in turn enhances students’ cognitive learning (i.e., active, interactive, constructive, and reflective learning) in class, further contributing to their enhanced cognitive CT abilities. The findings underscore the nuances of SCP adoption in school scenarios, advocating for strategic approaches to maximize student achievements in CT education. Recommendations for future research are discussed.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"215 ","pages":"Article 105016"},"PeriodicalIF":12.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140043792","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}
{"title":"Running in circles: A systematic review of reviews on technological pedagogical content knowledge (TPACK)","authors":"Mirjam Schmid , Eliana Brianza , Sog Yee Mok , Dominik Petko","doi":"10.1016/j.compedu.2024.105024","DOIUrl":"10.1016/j.compedu.2024.105024","url":null,"abstract":"<div><p>Extensive research exists on the Technological Pedagogical Content Knowledge (TPACK) model and has led to a substantial number of systematic reviews and meta-analyses. These publications vary greatly in their focus and provide overviews of specific aspects of TPACK research. This paper aims to consolidate these insights and investigate the following research questions: What do systematic literature reviews and meta-analyses reveal about the current state of the art of TPACK research? What is the methodological quality of systematic reviews and meta-analyses of TPACK? This study identified 21 systematic reviews and 2 meta-analyses eligible for analysis. Overall, the review of the reviews revealed that many of the recurring theoretical or methodological issues of the TPACK framework remain unresolved. To address these issues, research on TPACK needs to simultaneously account for the complex, situated, and dynamic nature of TPACK and clarify the concept of professional knowledge. The review engenders several directions for future research, including a better operationalization of knowledge, more experimental and longitudinal studies, and a more comprehensive measurement and integration of student learning as a dependent variable in research on TPACK.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"214 ","pages":"Article 105024"},"PeriodicalIF":12.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0360131524000381/pdfft?md5=2b51ef87f55cbca775552b5863783682&pid=1-s2.0-S0360131524000381-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140043713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of cluster analysis to identify different reader groups through their engagement with a digital reading supplement","authors":"Yawen Ma , Kate Cain , Anastasia Ushakova","doi":"10.1016/j.compedu.2024.105025","DOIUrl":"https://doi.org/10.1016/j.compedu.2024.105025","url":null,"abstract":"<div><p>The focus of this study is the identification of reader profiles that differ in performance and progression in an educational literacy app. A total of 19,830 students in Grade 2 from 347 Elementary schools located in 30 different districts in the United States played the app from 2020 to 2021. Our aim was to identify unique groups of readers using an unsupervised statistical learning technique - cluster analysis. Six indicators generated from the students<sup>’</sup> log files were included to provide insights into engagement and learning across four different reading-related skills: phonological awareness, early decoding, vocabulary, and comprehension processes. A key aim was to evaluate the implementation and performance of Gaussian mixture models, k-means, k-medoids, clustering large applications and hierarchical clustering, alongside provision of detailed guidance that can benefit researchers in the field. K-means algorithm performed the best and identified nine groups of readers. Children with low initial reading ability showed greater engagement with code-related games (phonological awareness, early decoding) and took longer to master these games, whereas children with higher initial ability showed more engagement with meaning-related games (vocabulary, comprehension processes). Our findings can inform further research that aims to understand individual differences in learning behaviour within digital environments both over time and across various cohorts of children.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"214 ","pages":"Article 105025"},"PeriodicalIF":12.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0360131524000393/pdfft?md5=5f43f478f4ab70426d8b3f1b46e7b08f&pid=1-s2.0-S0360131524000393-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140016009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}