Journal of Computer Assisted Learning最新文献

{"title":"The effectiveness of self-regulated learning strategies in higher education blended learning: A five years systematic review","authors":"Ren-Zhi Luo,&nbsp;Yue-Liang Zhou","doi":"10.1111/jcal.13052","DOIUrl":"10.1111/jcal.13052","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The COVID-19 has accelerated the transition to blended learning (BL) in higher education, prompting a need for further investigation into the efficacy of self-regulated learning strategies (SRLS) in these new educational environments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The primary goal of this research is to assess the effectiveness of SRLS in BL in higher education over the past five years, with a focus on trends, theoretical underpinnings, methodologies, and their impact on learning outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This paper used the PRISMA 2020 review process for multiple rounds of screening, encompassing identification, screening, eligibility determination, and final inclusion. Following rigorous screening procedures, a total of 15 SSCI articles were ultimately chosen for analysis. The study design incorporated a comprehensive six-part coding scheme, with the selected articles focusing on SRLS in BL environments within higher education.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>From 2019 to 2023, research on SRLS in BL environments in higher education has primarily focused on resource management, motivational beliefs, and metacognitive strategies, with a relatively limited emphasis on cognitive strategies. These studies have utilized a diverse range of theoretical frameworks, predominantly employing quantitative and mixed methods. Out of the 15 articles reviewed, 14 clearly indicate that SRLS have a positive impact on learning outcomes. Furthermore, this paper underscores the importance of interdisciplinary research and emphasizes the crucial role played by educators in supporting the implementation of SRLS. Future studies should delve deeper into exploring the effects of individual differences and environmental factors on SRLS.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"3005-3029"},"PeriodicalIF":5.1,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141932587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining students' self-regulated learning processes and performance in an immersive virtual environment","authors":"Yi-Fan Li,&nbsp;Jue-Qi Guan,&nbsp;Xiao-Feng Wang,&nbsp;Qu Chen,&nbsp;Gwo-Jen Hwang","doi":"10.1111/jcal.13047","DOIUrl":"10.1111/jcal.13047","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Self-regulated learning (SRL) is a predictive variable in students' academic performance, especially in virtual reality (VR) environments, which lack monitoring and control. However, current research on VR encounters challenges in effective interventions of cognitive and affective regulation, and visualising the SRL processes using multimodal data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study aimed to analyse multimodal data to investigate the SRL processes (behaviour, cognition and affective states) and learning performance in the VR environment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study developed a VR-based immersive learning system that supports SRL activities, and conducted a pilot study in an English for Geography course. A total of 21 undergraduates participated. Face tracker, electroencephalography, and learning logs were used to gather data for learning behaviour, cognition and affective states in the VR environment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>First, the study identified three categories of learners (HG, MG and LG) within the VR environment who presented different behavioural engagement and SRL strategies. The HG exhibited the highest level of cognition and affective states, which resulted in superior performance in terms of vocabulary acquisition and retention. The MG, despite possessing a higher level of cognition, performed inadequately in other aspects, leading to no difference in vocabulary acquisition and retention from the LG. By collecting and mining multimodal data, this study helps to enrich the visual analysis of SRL processes. In addition, the results of this study help to dissect the problems of students' SRL in a VR learning environment. Furthermore, this study provides a theoretical basis and reference for the study of SRL development in immersive learning environments.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2948-2963"},"PeriodicalIF":5.1,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885399","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}

{"title":"Flight emotions unleashed: Navigating training phases and difficulty levels in simulated flying","authors":"Alejandra Ruiz-Segura,&nbsp;Andrew Law,&nbsp;Sion Jennings,&nbsp;Alain Bourgon,&nbsp;Ethan Churchill,&nbsp;Susanne Lajoie","doi":"10.1111/jcal.13037","DOIUrl":"10.1111/jcal.13037","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task-related emotions and flying performance is needed to enhance pilot training.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight simulator.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Twenty-three volunteers performed basic flight manoeuvres. Trials were divided into three phases: Introduction (trials 1–7), session A (trials 8–15) and session B (trials 16–22). Three task difficulty levels were implemented (low, medium and high). Flying performance was evaluated using root mean square error (RMSE) and expert ratings. Emotional intensity was inferred from physiological (electrodermal activity) and behavioural (facial expressions) emotional responses. Emotional variability was calculated to understand fluctuations among multiple emotions. Emotional responses were mapped into task-relevant emotions, like sadness with boredom, and fear with anxiety.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>The most frequent facial expressions neutral, anger and surprise. Neutral and anger were interpreted as deep focus states. Surprise was likely a response to unexpected events. Flying performance and emotional dynamics varied across training phases and difficulty levels. During introduction, performance was less accurate, and emotions were less frequent. During session A, performance improved while participants experienced more physiological arousal and emotional variability. During session B, performance was the most accurate. In high-difficulty tasks, performance was the least accurate, participants expressed emotions with more frequency, more variability and higher physiological arousal. Future studies can use simulated flying tasks for trainees to familiarize with their emotional reactions to task demands expecting to improve training outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2926-2947"},"PeriodicalIF":5.1,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early artificial intelligence education: Effects of cooperative play and direct instruction on kindergarteners' computational thinking, sequencing, self-regulation and theory of mind skills","authors":"Jiahong Su,&nbsp;Weipeng Yang,&nbsp;Iris Heung Yue Yim,&nbsp;Hui Li,&nbsp;Xiao Hu","doi":"10.1111/jcal.13040","DOIUrl":"10.1111/jcal.13040","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>While the integration of robot-based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>The study explored the effectiveness of two AI education approaches in advancing kindergarteners' computational thinking, sequencing, self-regulation and theory of mind skills.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An experiment was conducted with 90 kindergarteners (ages 5–6) randomly assigned to either a direct instruction (DI), cooperative play (CP) or control group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Results show that (1) children in all three groups had significant improvements on computational thinking, sequencing and self-regulation; (2) both early AI education approaches (CP and DI) significantly enhance young children's computational thinking, sequencing, self-regulation and theory of mind skills; (3) the DI group had significant higher improvement than the CP group on computational thinking; (4) the CP group exhibited greater enhancements in theory of mind skills than the DI group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These findings jointly demonstrate that each AI educational approach has unique strengths, underscoring the significance of designing new pedagogies to expand children's skills.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2917-2925"},"PeriodicalIF":5.1,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model for assessing student satisfaction with smart classroom environment in higher education","authors":"Zhicheng Dai,&nbsp;Ling Wang,&nbsp;Xian Peng,&nbsp;Liang Zhao,&nbsp;Junxia Xiong","doi":"10.1111/jcal.13045","DOIUrl":"10.1111/jcal.13045","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Smart classroom environment has drawn worldwide attention, however, there is still a lack of studies that can explore and analyse potential factors, which affect students' satisfaction with smart classrooms in higher education.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To assess students' satisfaction with smart classrooms in higher education, this study proposed the smart classroom environment satisfaction model based on TAM and ACSI models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A sample of 1979 Chinese college students who studied in a smart classroom environment completed a survey assessing student satisfaction with the smart classroom environment. And a structural equation modelling analysis was used to further analyse students' preferences for smart classroom environments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and conclusions</h3>\u0000 \u0000 <p>The results showed that student satisfaction with smart classroom environment is significantly correlated with subjective perception factors after use, such as students' perceived value (PV), user experience and perceived expectations (PE). It indicated that user experience indirectly affected overall satisfaction (OS) through its positive impact on PV, while PE indirectly affected OS through its positive impact on user experience. Second, user experience had the greatest impact on student satisfaction, followed by PV and PE. This study is a theoretical supplement to future research on smart classroom environment in higher education, and can also provide reference for relevant government departments, universities and enterprises to build and manage smart classroom environment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2901-2916"},"PeriodicalIF":5.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810186","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}

{"title":"The relationship between students' self-regulated learning behaviours and problem-solving efficiency in technology-rich learning environments","authors":"Tingting Wang,&nbsp;Alejandra Ruiz-Segura,&nbsp;Shan Li,&nbsp;Susanne P. Lajoie","doi":"10.1111/jcal.13043","DOIUrl":"10.1111/jcal.13043","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Scholars have confirmed the vital roles of self-regulated learning (SRL) behaviours in predicting task performance, especially within non-linear technology-rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time-on-task) related to SRL and the efficiency outcome of SRL (i.e., the relative relationship between learning costs and performance).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study examined the relationship between students' SRL behaviours and problem-solving efficiency in the context of TREs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Eighty-two medical students accomplished a diagnostic task in a computer-simulated environment, and they were classified into the efficient or less efficient group according to diagnostic performance and time-on-task. Then we coded students' SRL behaviours from trace data and counted the frequency of each SRL behaviour. The recurrence quantification and lag sequential analyses were performed to extract the dynamic characteristics of SRL behaviours, including recurrent patterns and sequential transitions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Efficient students conducted more frequent Self-reflection behaviours than the less efficient. For the recurrent patterns, efficient students tended to exhibit longer SRL behaviour sequences comprising a variety of different SRL behaviours (e.g., Task Analysis &gt; Add Test &gt; Add Hypotheses &gt; Categorise Evidence) as well as longer sequences of repeated SRL behaviours (e.g., Add Test &gt; Add Test &gt; Add Test &gt; Add Test). Moreover, efficient students exhibited more sequential transitions between different SRL behaviours than less efficient.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Takeaways</h3>\u0000 \u0000 <p>Overall, this study revealed the effects of SRL on problem-solving efficiency, which inspired researchers to incorporate problem-solving efficiency as an evaluation criterion of SRL processes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2886-2900"},"PeriodicalIF":5.1,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781375","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}

{"title":"Educational policy as predictor of computational thinking: A supervised machine learning approach","authors":"Ndudi O. Ezeamuzie,&nbsp;Jessica S. C. Leung,&nbsp;Dennis C. L. Fung,&nbsp;Mercy N. Ezeamuzie","doi":"10.1111/jcal.13041","DOIUrl":"10.1111/jcal.13041","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational policies on computational thinking remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This study examines the impact of basic and technology-related educational policies on the development of computational thinking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using supervised machine learning, the computational thinking achievements of 31,823 eighth graders across nine countries were analysed. Seven rule-based and tree-based classification models were generated and triangulated to determine how educational policies predicted students' computational thinking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and conclusions</h3>\u0000 \u0000 <p>Predictions show that students have a higher propensity to develop computational thinking skills when schools exercise full autonomy in governance and explicitly embed computational thinking in their curriculum. Plans to support students, teachers and schools with technology or introduce 1:1 computing have no discernible predicted influence on students' computational thinking achievement.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Implications</h3>\u0000 \u0000 <p>Although predictions deduced from these attributes are not generalizable, traces of how educational policies affect computational thinking exist to articulate more fronts for future research on the influence of educational policies on computational thinking.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2872-2885"},"PeriodicalIF":5.1,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745114","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}

{"title":"Learning analytics dashboard design: Workplace learner preferences for reference frames in immersive training in practice","authors":"Timothy Gallagher,&nbsp;Bert Slof,&nbsp;Marieke van der Schaaf,&nbsp;Michaela Arztmann,&nbsp;Sofia Garcia Fracaro,&nbsp;Liesbeth Kester","doi":"10.1111/jcal.13042","DOIUrl":"10.1111/jcal.13042","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Learning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self-regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self-reflection phases) and SRL skills. Insight into design preferences for dashboards with different reference frames (i.e., progress, social, internal achievement and external achievement) is important because the effectiveness of feedback can depend upon how a learner perceives it.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study examines workplace learner preferences for four dashboard designs for each SRL phase and how SRL skills relate to these preferences.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Seventy participants enrolled in a chemical process apprenticeship program took part in the study. Preferences were determined using a method of adaptive comparative judgement and SRL skills were measured using a questionnaire. Preferences were tested on four dashboard designs informed by social and temporal comparison theory and goal setting theory. Multinomial logistic regressions were used to examine the relationship between dashboard preferences and SRL.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>Results show that the progress reference frame is more preferred before and after task performance, and the social reference frame is less preferred before and after task performance. It was found that the higher the SRL skill score the higher the probability a learner preferred the progress reference frame compared to having no preference before task performance. The results are consistent with other findings, which suggest caution when using social comparison in designing dashboards which provide feedback.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2840-2855"},"PeriodicalIF":5.1,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning with videos: Do task instructions and the availability of a pause button matter?","authors":"Martin Merkt,&nbsp;Daniel Bodemer","doi":"10.1111/jcal.13044","DOIUrl":"10.1111/jcal.13044","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>When watching educational online videos, learners need to determine whether the videos' contents are suitable for learning. Whereas this may induce metacognitive monitoring processes, it may also distract learners from the learning materials.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>In the current set of experiments, we investigated whether asking participants to rate the suitability of three educational videos to impart knowledge (both experiments) and enabling participants to pause the video (Experiment 2) affects learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Experiment 1 was conducted in the laboratory with a sample of university students. Participants were randomly assigned to one of two experimental conditions (rating task vs. viewing task). Experiment 2 was conducted online. Participants were randomly assigned to one of four conditions resulting from the two factors task (rating task vs. viewing task) and pause button (available vs. not available).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusion</h3>\u0000 \u0000 <p>In Experiment 1, we observed detrimental effects of the rating task on learning outcomes, but more accurate judgements of learning. In Experiment 2, we did not find any effects of the rating task on learning outcomes and the accuracy of the participants' judgements of learning. However, the inclusion of a pause button did result in more accurate judgements of learning. Further, exploratory analyses revealed that older participants reported higher levels of intrinsic and germane cognitive load than the younger participants. This increased effort only translated into better learning outcomes in the condition in that participants could pause the video. Thus, age is introduced as a potential boundary condition that should be investigated in instructional design research.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2856-2871"},"PeriodicalIF":5.1,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facilitating learners' self-assessment during formative writing tasks using writing analytics toolkit","authors":"Luzhen Tang,&nbsp;Kejie Shen,&nbsp;Huixiao Le,&nbsp;Yuan Shen,&nbsp;Shufang Tan,&nbsp;Yueying Zhao,&nbsp;Torsten Juelich,&nbsp;Xinyu Li,&nbsp;Dragan Gašević,&nbsp;Yizhou Fan","doi":"10.1111/jcal.13036","DOIUrl":"10.1111/jcal.13036","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Learners' writing skills are critical to their academic and professional development. Previous studies have shown that learners' self-assessment during writing is essential for assessing their writing products and monitoring their writing processes. However, conducting practical self-assessments of writing remains challenging for learners without help, such as formative feedback.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To facilitate learners' self-assessment in writing, we developed a writing analytics toolkit and used data visualisation and cutting-edge machine learning technology that provides real-time and formative feedback to learners.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To investigate whether our newly-developed tool affects the accuracy and process of learners' self-assessment, we conducted a lab study. We assigned 59 learners to complete writing (2 h) and revising (1 h) tasks. During the revision stage, we randomly assigned the learners to two groups: one group used the writing analytics toolkit while the second group was not granted access to the toolkit. Learners' self-assessment accuracy and process of self-assessment were compared between the two groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In our study, we found the toolkit helped learners in the experimental group improve the self-assessment accuracy of their writing products compared to the learners in the control group. In addition, we also found that the affordances of the toolkit affected the learners' self-assessment process, and poor design affordances may have prevented the learners from reflecting by themselves.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Together, our empirical study shed light on the design of future writing analytics tools which aim at improving learners' self-assessment during formative writing processes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2822-2839"},"PeriodicalIF":5.1,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}