The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool, EduNERScore, which enables raters to identify different types of domain knowledge from unstructured educational texts and strengthen the interpretation of assessment through knowledge-aware evidence. This research uses an educational experiment to examine raters’ validity, efficiency, interpretability and user perception with and without the support of EduNERScore. The findings show that the experimental group with the support of EduNERScore achieves human-expert validity, high efficiency, interpretability and good use perception, compared with the control group. Finally, based on the empirical results, this research discusses the technological and educational implications for developing and applying the interpretable CSWA system in education.
{"title":"Examining the Effects of a Real-Time, Knowledge-Aware Tool for Academic Writing Assessment","authors":"Xu Li, Ouyang Fan, Jianwen Liu, Chengkun Wei, Wenzhi Chen","doi":"10.1177/07356331221136889","DOIUrl":"https://doi.org/10.1177/07356331221136889","url":null,"abstract":"The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool, EduNERScore, which enables raters to identify different types of domain knowledge from unstructured educational texts and strengthen the interpretation of assessment through knowledge-aware evidence. This research uses an educational experiment to examine raters’ validity, efficiency, interpretability and user perception with and without the support of EduNERScore. The findings show that the experimental group with the support of EduNERScore achieves human-expert validity, high efficiency, interpretability and good use perception, compared with the control group. Finally, based on the empirical results, this research discusses the technological and educational implications for developing and applying the interpretable CSWA system in education.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"1143 - 1174"},"PeriodicalIF":4.8,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45248497","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 : 2023-03-16DOI: 10.1177/07356331221133560
Xuemin Gao, K. Hew
Reintroducing computer science (CS) education in K–12 schools to promote computational thinking (CT) has attracted significant attention among scholars and educators. Among the several essential components included in CS and CT education, program debugging is an indispensable skill. However, debugging teaching has often been overlooked in K–12 contexts, and relevant empirical studies are lacking in the literature. Moreover, novices generally have poor performance in domain knowledge and strategic knowledge concerning debugging. They also consistently experience a high cognitive burden in debugging learning. To address these gaps, we developed a flipped systematic debugging approach combined with a systematic debugging process (SDP) and the modeling method. A quasi-experimental study was conducted to explore the effectiveness of this flipped systematic debugging approach, in which 83 fifth-grade students attended the flipped debugging training lessons with the SDP–modeling method, and 75 fifth-grade students attended the unassisted flipped debugging training lessons without the SDP–modeling method. The results indicated that flipped debugging training using the SDP–modeling method improved students’ debugging skills. The results from the questionnaire showed that the proposed teaching approach increased the students’ investment in germane cognitive load by promoting schema construction. It also helped reduce students’ intrinsic and extraneous cognitive load in learning.
{"title":"A Flipped Systematic Debugging Approach to Enhance Elementary Students’ Program Debugging Performance and Optimize Cognitive Load","authors":"Xuemin Gao, K. Hew","doi":"10.1177/07356331221133560","DOIUrl":"https://doi.org/10.1177/07356331221133560","url":null,"abstract":"Reintroducing computer science (CS) education in K–12 schools to promote computational thinking (CT) has attracted significant attention among scholars and educators. Among the several essential components included in CS and CT education, program debugging is an indispensable skill. However, debugging teaching has often been overlooked in K–12 contexts, and relevant empirical studies are lacking in the literature. Moreover, novices generally have poor performance in domain knowledge and strategic knowledge concerning debugging. They also consistently experience a high cognitive burden in debugging learning. To address these gaps, we developed a flipped systematic debugging approach combined with a systematic debugging process (SDP) and the modeling method. A quasi-experimental study was conducted to explore the effectiveness of this flipped systematic debugging approach, in which 83 fifth-grade students attended the flipped debugging training lessons with the SDP–modeling method, and 75 fifth-grade students attended the unassisted flipped debugging training lessons without the SDP–modeling method. The results indicated that flipped debugging training using the SDP–modeling method improved students’ debugging skills. The results from the questionnaire showed that the proposed teaching approach increased the students’ investment in germane cognitive load by promoting schema construction. It also helped reduce students’ intrinsic and extraneous cognitive load in learning.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"1064 - 1095"},"PeriodicalIF":4.8,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43185770","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 : 2023-03-01DOI: 10.1177/07356331221103764
Hanxiang Du, Wanli Xing, Gaoxia Zhu
Social-media-based teacher learning networks have the affordance to grant flexibility of time and space for teachers’ professional learning, support the development and sustainability of social networking, and meet their just-in-time needs for exchanging knowledge, negotiating meaning and accessing resources. However, most existing research on teacher online learning networks relies on qualitative methods and self-report data. There is a lack of study using quantitative methods to study large networks, especially using authentic data from social media. This work adds to the literature through mining teacher informal online learning networks using authentic data retrieved from Twitter. Specifically, we collected around half a million tweets and developed a network with the data. Then, various social network analysis techniques were utilized to explore the network structure and characteristics, participants’ behavioral patterns and how individuals connected with each other. We found that members of massive teacher informal online learning networks tended to communicate more with others of similar characteristics forming homogeneous communities, while hub participants connected many small communities which are significantly from one another, and hence, are the key to degree heterogeneity in a large network.
{"title":"Mining Teacher Informal Online Learning Networks: Insights From Massive Educational Chat Tweets","authors":"Hanxiang Du, Wanli Xing, Gaoxia Zhu","doi":"10.1177/07356331221103764","DOIUrl":"https://doi.org/10.1177/07356331221103764","url":null,"abstract":"Social-media-based teacher learning networks have the affordance to grant flexibility of time and space for teachers’ professional learning, support the development and sustainability of social networking, and meet their just-in-time needs for exchanging knowledge, negotiating meaning and accessing resources. However, most existing research on teacher online learning networks relies on qualitative methods and self-report data. There is a lack of study using quantitative methods to study large networks, especially using authentic data from social media. This work adds to the literature through mining teacher informal online learning networks using authentic data retrieved from Twitter. Specifically, we collected around half a million tweets and developed a network with the data. Then, various social network analysis techniques were utilized to explore the network structure and characteristics, participants’ behavioral patterns and how individuals connected with each other. We found that members of massive teacher informal online learning networks tended to communicate more with others of similar characteristics forming homogeneous communities, while hub participants connected many small communities which are significantly from one another, and hence, are the key to degree heterogeneity in a large network.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"127 - 150"},"PeriodicalIF":4.8,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45872522","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 : 2023-02-03DOI: 10.1177/07356331221138734
Yi Song, Mengxiao Zhu, Jesse R. Sparks
In this research, we use a process data analysis approach to gather additional evidence about students’ argumentation skills beyond their performance scores in a computer-based assessment. This game-enhanced scenario-based assessment (named Seaball) included five activities that require students to demonstrate their argumentation skills within a scenario about whether junk food should be sold to students. Our research sample included 104 middle school students. Process data analyses focused on an “Interview” activity in which students explored different locations and interviewed various characters to identify their opinions on the junk food issue and categorize each opinion as pro or con. Students could take various paths to complete the activity. Results indicated that the number of trials students made in the Interview activity predicted their performance on the Interview activity as well as the total Seaball scores. It was also found that most students improved their answers in the Interview activity after receiving automated feedback and making corresponding changes. Besides the connections between student activities and performance, results from analyzing the process data helped us to identify difficult items in the task. We conclude with implications for conducting process data analysis to better assess students’ argumentation skills and to inform task design.
{"title":"Exploring the Role of Process Data Analysis in Understanding Student Performance and Interactive Behavior in a Game-Based Argument Task","authors":"Yi Song, Mengxiao Zhu, Jesse R. Sparks","doi":"10.1177/07356331221138734","DOIUrl":"https://doi.org/10.1177/07356331221138734","url":null,"abstract":"In this research, we use a process data analysis approach to gather additional evidence about students’ argumentation skills beyond their performance scores in a computer-based assessment. This game-enhanced scenario-based assessment (named Seaball) included five activities that require students to demonstrate their argumentation skills within a scenario about whether junk food should be sold to students. Our research sample included 104 middle school students. Process data analyses focused on an “Interview” activity in which students explored different locations and interviewed various characters to identify their opinions on the junk food issue and categorize each opinion as pro or con. Students could take various paths to complete the activity. Results indicated that the number of trials students made in the Interview activity predicted their performance on the Interview activity as well as the total Seaball scores. It was also found that most students improved their answers in the Interview activity after receiving automated feedback and making corresponding changes. Besides the connections between student activities and performance, results from analyzing the process data helped us to identify difficult items in the task. We conclude with implications for conducting process data analysis to better assess students’ argumentation skills and to inform task design.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"1096 - 1120"},"PeriodicalIF":4.8,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47780252","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 : 2023-01-30DOI: 10.1177/07356331231151393
Pavlos Toukiloglou, S. Xinogalos
Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback. A support design that evaluates students’ progress and adapts accordingly, has the potential of producing better learning results. This paper presents an adaptive model based on fuzzy logic that adjusts the support acquisition according to student knowledge level. A serious game for teaching the concepts of sequence and iteration in programming to novice students was built to assess the model. It employs working examples as a support method since previous research indicated that it produced less cognitive load during problem-solving. An empirical study with 102 students has been conducted to evaluate the learning efficiency of the model. The analysis indicates positive results and a potential solution for balancing the amount of assistance in serious games.
{"title":"Adaptive Support With Working Examples in Serious Games About Programming","authors":"Pavlos Toukiloglou, S. Xinogalos","doi":"10.1177/07356331231151393","DOIUrl":"https://doi.org/10.1177/07356331231151393","url":null,"abstract":"Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback. A support design that evaluates students’ progress and adapts accordingly, has the potential of producing better learning results. This paper presents an adaptive model based on fuzzy logic that adjusts the support acquisition according to student knowledge level. A serious game for teaching the concepts of sequence and iteration in programming to novice students was built to assess the model. It employs working examples as a support method since previous research indicated that it produced less cognitive load during problem-solving. An empirical study with 102 students has been conducted to evaluate the learning efficiency of the model. The analysis indicates positive results and a potential solution for balancing the amount of assistance in serious games.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"766 - 789"},"PeriodicalIF":4.8,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41888606","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}
Given the inadequacy of assessed outcomes (e.g., final exam) and the importance of evaluating the learning process in STEM education, we use deep learning to develop the STEM learning behavior analysis system (SLBAS) to assess the behavior of learners in STEM education. We map learner behavior to the ICAP (interactive, constructive, active, passive) framework, helping instructors to better understand the learning process of learners. The results show that SLBAS exhibits high accuracy. Moreover, Cohen’s kappa coefficient between expert coding and SLBAS is high enough to support replacing expert coding in the observation method with SLBAS to recognize the learning process of learners during STEM activities. Finally, statistical analysis establishes a correlation between the learning process and learning effectiveness. The results of this study are in line with most previous studies, demonstrating that STEM education differs from traditional teacher-centered courses in that it helps learners to improve the process of knowledge construction with practice and hands-on opportunities rather than simply receiving knowledge passively.
{"title":"Exploring the Learning Process and Effectiveness of STEM Education via Learning Behavior Analysis and the Interactive-Constructive- Active-Passive Framework","authors":"Hsin-Yu Lee, Yu-Ping Cheng, Wei-Sheng Wang, Chia-Ju Lin, Yueh-Min Huang","doi":"10.1177/07356331221136888","DOIUrl":"https://doi.org/10.1177/07356331221136888","url":null,"abstract":"Given the inadequacy of assessed outcomes (e.g., final exam) and the importance of evaluating the learning process in STEM education, we use deep learning to develop the STEM learning behavior analysis system (SLBAS) to assess the behavior of learners in STEM education. We map learner behavior to the ICAP (interactive, constructive, active, passive) framework, helping instructors to better understand the learning process of learners. The results show that SLBAS exhibits high accuracy. Moreover, Cohen’s kappa coefficient between expert coding and SLBAS is high enough to support replacing expert coding in the observation method with SLBAS to recognize the learning process of learners during STEM activities. Finally, statistical analysis establishes a correlation between the learning process and learning effectiveness. The results of this study are in line with most previous studies, demonstrating that STEM education differs from traditional teacher-centered courses in that it helps learners to improve the process of knowledge construction with practice and hands-on opportunities rather than simply receiving knowledge passively.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"951 - 976"},"PeriodicalIF":4.8,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43859317","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 : 2023-01-28DOI: 10.1177/07356331221137107
Rushi Yu, Meishu Wang, Jie Hu
The age of information and communication technology (ICT) has witnessed the prevalence of computer-based reading. Previous studies yielded mixed results concerning the relationship between ICT perceived competence, ICT use and digital reading performance, and the underlying mechanism was rarely explored. This study aimed to explore the relationship between ICT perceived competence and adolescents’ digital reading performance and the potential mediating roles of three types of ICT use. Multilevel mediation analyses were conducted for 199,646 15-year-old students from 29 OECD countries/regions in the Programme for International Student Assessment (PISA) 2018, in which digital reading performance was assessed by multistage adaptive computer-based testing. The results revealed that a) ICT perceived competence and digital reading performance were positively correlated; b) ICT use significantly mediated the relationship; c) students with higher-level ICT perceived competence tended to use ICT for leisure at home more frequently, which led to better digital reading performance; d) the suppression effects were revealed, indicating the need to consider the interrelationship between ICT perceived competence and ICT use. These findings provided new evidence for the self-determination theory and the ICT engagement model, suggesting that appropriate ICT use driven by high-level ICT perceived competence might help improve adolescents’ digital reading performance.
{"title":"The Relationship Between ICT Perceived Competence and Adolescents’ Digital Reading Performance: A Multilevel Mediation Study","authors":"Rushi Yu, Meishu Wang, Jie Hu","doi":"10.1177/07356331221137107","DOIUrl":"https://doi.org/10.1177/07356331221137107","url":null,"abstract":"The age of information and communication technology (ICT) has witnessed the prevalence of computer-based reading. Previous studies yielded mixed results concerning the relationship between ICT perceived competence, ICT use and digital reading performance, and the underlying mechanism was rarely explored. This study aimed to explore the relationship between ICT perceived competence and adolescents’ digital reading performance and the potential mediating roles of three types of ICT use. Multilevel mediation analyses were conducted for 199,646 15-year-old students from 29 OECD countries/regions in the Programme for International Student Assessment (PISA) 2018, in which digital reading performance was assessed by multistage adaptive computer-based testing. The results revealed that a) ICT perceived competence and digital reading performance were positively correlated; b) ICT use significantly mediated the relationship; c) students with higher-level ICT perceived competence tended to use ICT for leisure at home more frequently, which led to better digital reading performance; d) the suppression effects were revealed, indicating the need to consider the interrelationship between ICT perceived competence and ICT use. These findings provided new evidence for the self-determination theory and the ICT engagement model, suggesting that appropriate ICT use driven by high-level ICT perceived competence might help improve adolescents’ digital reading performance.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"817 - 846"},"PeriodicalIF":4.8,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42842221","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 : 2023-01-23DOI: 10.1177/07356331221133822
Ana Melro, G. Tarling, T. Fujita, Judith Kleine Staarman
Underpinning the teaching of coding with Computational Thinking has proved relevant for diverse learners, particularly given the increasing demand in upskilling for today’s labour market. While literature on computing education is vast, it remains unexplored how existing CT conceptualisations relate to the learning opportunities needed for a meaningful application of coding in non-Computer Scientists’ lives and careers. In order to identify and organise the learning opportunities in the literature about CT, we conducted a configurative literature review of studies published on Web of Science, between 2006 and 2021. Our sample gathers 34 papers and was analysed on NVivo to find key themes. We were able to organise framings of CT and related learning opportunities into three dimensions: functional, collaborative, and critical and creative. These dimensions make visible learning opportunities that range from individual cognitive development to interdisciplinary working with others, and to active participation in a technologically evolving society. By comparing and contrasting frameworks, we identify and explain different perspectives on skills. Furthermore, the three-dimensional model can guide pedagogical design and practice in coding courses.
事实证明，以计算思维为基础的编码教学与不同的学习者息息相关，特别是考虑到当今劳动力市场对提高技能的需求不断增加。虽然有关计算机教育的文献大量，但仍未探索现有的CT概念如何与非计算机科学家的生活和职业中有意义的编码应用所需的学习机会联系起来。为了识别和组织有关CT的文献中的学习机会，我们对2006年至2021年间发表在Web of Science上的研究进行了配置性文献综述。我们的样本收集了34篇论文，并在NVivo上进行了分析，以找到关键主题。我们能够将CT的框架和相关的学习机会组织到三个维度:功能性、协作性、批判性和创造性。这些维度提供了可见的学习机会，从个人认知发展到与他人跨学科合作，以及积极参与技术不断发展的社会。通过比较和对比框架，我们确定并解释了关于技能的不同观点。此外，三维模型可以指导编程课程的教学设计和实践。
{"title":"What Else Can Be Learned When Coding? A Configurative Literature Review of Learning Opportunities Through Computational Thinking","authors":"Ana Melro, G. Tarling, T. Fujita, Judith Kleine Staarman","doi":"10.1177/07356331221133822","DOIUrl":"https://doi.org/10.1177/07356331221133822","url":null,"abstract":"Underpinning the teaching of coding with Computational Thinking has proved relevant for diverse learners, particularly given the increasing demand in upskilling for today’s labour market. While literature on computing education is vast, it remains unexplored how existing CT conceptualisations relate to the learning opportunities needed for a meaningful application of coding in non-Computer Scientists’ lives and careers. In order to identify and organise the learning opportunities in the literature about CT, we conducted a configurative literature review of studies published on Web of Science, between 2006 and 2021. Our sample gathers 34 papers and was analysed on NVivo to find key themes. We were able to organise framings of CT and related learning opportunities into three dimensions: functional, collaborative, and critical and creative. These dimensions make visible learning opportunities that range from individual cognitive development to interdisciplinary working with others, and to active participation in a technologically evolving society. By comparing and contrasting frameworks, we identify and explain different perspectives on skills. Furthermore, the three-dimensional model can guide pedagogical design and practice in coding courses.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"901 - 924"},"PeriodicalIF":4.8,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48456340","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 : 2023-01-19DOI: 10.1177/07356331221137253
Wu-Yuin Hwang, R. Nurtantyana, Siska Wati Dewi Purba, U. Hariyanti, Y. Indrihapsari, Herman Dwi Surjono
English as Foreign Language (EFL) writing is challenging for students due to the lack of related lexical resources to inspire them for meaningful writing besides grammar feedback. Moreover, it is crucial to design personalized feedback based on students’ original writings in helping to improve their writing abilities. Therefore, we developed Smart RoamLingo app to help writing meaningful content in authentic contexts with sample sentences based on texts generated by recognition technologies named as AI-Sample Sentences (AI-SS) and writing qualities with revision suggestions based on personal original writings named as AI-Writing Feedback (AI-WF). 104 undergraduate students were assigned into an experimental group (EG) and two control groups. EG significantly outperformed the other groups in the post-test. In EG, AI-SS can help the contextualization to produce comprehensive content actively while AI-WF can help the personalization to improve the writing quality through several revisions. Hence, the cohesion and consistency of their writing can be enhanced. Further, the total number of revisions in practices and the assignment score can significantly predict the post-test. Moreover, EG students revealed that Smart RoamLingo was useful for EFL writing. Therefore, it is strongly suggested to use Smart RoamLingo with AI-SS and AI-WF for EFL writing in authentic contexts.
{"title":"AI and Recognition Technologies to Facilitate English as Foreign Language Writing for Supporting Personalization and Contextualization in Authentic Contexts","authors":"Wu-Yuin Hwang, R. Nurtantyana, Siska Wati Dewi Purba, U. Hariyanti, Y. Indrihapsari, Herman Dwi Surjono","doi":"10.1177/07356331221137253","DOIUrl":"https://doi.org/10.1177/07356331221137253","url":null,"abstract":"English as Foreign Language (EFL) writing is challenging for students due to the lack of related lexical resources to inspire them for meaningful writing besides grammar feedback. Moreover, it is crucial to design personalized feedback based on students’ original writings in helping to improve their writing abilities. Therefore, we developed Smart RoamLingo app to help writing meaningful content in authentic contexts with sample sentences based on texts generated by recognition technologies named as AI-Sample Sentences (AI-SS) and writing qualities with revision suggestions based on personal original writings named as AI-Writing Feedback (AI-WF). 104 undergraduate students were assigned into an experimental group (EG) and two control groups. EG significantly outperformed the other groups in the post-test. In EG, AI-SS can help the contextualization to produce comprehensive content actively while AI-WF can help the personalization to improve the writing quality through several revisions. Hence, the cohesion and consistency of their writing can be enhanced. Further, the total number of revisions in practices and the assignment score can significantly predict the post-test. Moreover, EG students revealed that Smart RoamLingo was useful for EFL writing. Therefore, it is strongly suggested to use Smart RoamLingo with AI-SS and AI-WF for EFL writing in authentic contexts.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"1008 - 1035"},"PeriodicalIF":4.8,"publicationDate":"2023-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46577886","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 : 2023-01-15DOI: 10.1177/07356331221139859
Noah L. Schroeder, Erin K. Chiou, Robert F. Siegle, Scotty D. Craig
Virtual humans are on-screen characters that are often embedded in learning technologies to deliver educational content. Little research has investigated how virtual humans can be used to correct common misconceptions. In this study, we explored how different types of narrative structures, refutation text and expository text, influence perceptions of trust, credibility, and learning outcomes. In addition, we conducted exploratory analyses examining how different measures of trust and credibility are related to each other and how these measures may mediate learning outcomes. Results showed that the type of narrative used did not influence any measure. However, the trust and credibility measures, while related to one another, were measurably distinct. In addition, only perceptions of message trust were significantly related to learning. Perceptions of message trust did not mediate learning outcomes, but were significantly predictive of learning at nearly the same effect as prior knowledge.
{"title":"Trusting and Learning From Virtual Humans that Correct Common Misconceptions","authors":"Noah L. Schroeder, Erin K. Chiou, Robert F. Siegle, Scotty D. Craig","doi":"10.1177/07356331221139859","DOIUrl":"https://doi.org/10.1177/07356331221139859","url":null,"abstract":"Virtual humans are on-screen characters that are often embedded in learning technologies to deliver educational content. Little research has investigated how virtual humans can be used to correct common misconceptions. In this study, we explored how different types of narrative structures, refutation text and expository text, influence perceptions of trust, credibility, and learning outcomes. In addition, we conducted exploratory analyses examining how different measures of trust and credibility are related to each other and how these measures may mediate learning outcomes. Results showed that the type of narrative used did not influence any measure. However, the trust and credibility measures, while related to one another, were measurably distinct. In addition, only perceptions of message trust were significantly related to learning. Perceptions of message trust did not mediate learning outcomes, but were significantly predictive of learning at nearly the same effect as prior knowledge.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"790 - 816"},"PeriodicalIF":4.8,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41913781","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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