Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00069
Mohammad Karimzadeh, H. Jamil
A simple way to assess the correctness of a student’s SQL query is to compare results with a correct query for equality. Technically, the two queries will produce identical responses only if they are computationally equivalent. Until recently, establishing such equality largely tested set equality of the returned results at great computational cost with not enough confidence. In most e-Learning systems, providing feedback to improve learning has remained illusive in a setup where no semantic foundation was used to assess the query. In this paper, we present a new e-Learning platform for SQL, called ViSQL, that combines teaching, tutoring and assessment in one single system. We leverage recent development of a query equivalence solver to craft mentoring strategies using automated feedback and guidance to aid learning and scale learner support.
{"title":"ViSQL: An Intelligent Online SQL Tutoring System","authors":"Mohammad Karimzadeh, H. Jamil","doi":"10.1109/ICALT55010.2022.00069","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00069","url":null,"abstract":"A simple way to assess the correctness of a student’s SQL query is to compare results with a correct query for equality. Technically, the two queries will produce identical responses only if they are computationally equivalent. Until recently, establishing such equality largely tested set equality of the returned results at great computational cost with not enough confidence. In most e-Learning systems, providing feedback to improve learning has remained illusive in a setup where no semantic foundation was used to assess the query. In this paper, we present a new e-Learning platform for SQL, called ViSQL, that combines teaching, tutoring and assessment in one single system. We leverage recent development of a query equivalence solver to craft mentoring strategies using automated feedback and guidance to aid learning and scale learner support.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124898660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00040
A. H. Metwally, A. Tlili, A. Yousef, Ronghuai Huang, L. Nacke
The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.
{"title":"Empirical Evidence on Gamification and Learning Analytics (GaLA): What is Missing?","authors":"A. H. Metwally, A. Tlili, A. Yousef, Ronghuai Huang, L. Nacke","doi":"10.1109/ICALT55010.2022.00040","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00040","url":null,"abstract":"The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125893216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00007
J. Choi, S. Crossley
Readability research and the entailing derivation of theoretically valid and high-performing readability assessment models are important components of reading education. There have been notable advances in the research of readability assessment following the advances of natural language processing techniques. Specifically, newer formulas make use of complex linguistic features that were previously unavailable, as well as contextually representative word-embeddings derived by training neural networks. However, there remain limitations for newer readability formulas, especially with respect to the employment of newer formulas by educational content creators. This paper provides an overview of readability research and introduces a new web app to help facilitate the application of state-of-the-art readability formulas for educational content creators and researchers through both an online interface and a separate API. An increase in accessibility and exposure for state-of-the-art readability formulas will assist in addressing many limitations of integrating readability research into educational technologies.
{"title":"Advances in Readability Research: A New Readability Web App for English","authors":"J. Choi, S. Crossley","doi":"10.1109/ICALT55010.2022.00007","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00007","url":null,"abstract":"Readability research and the entailing derivation of theoretically valid and high-performing readability assessment models are important components of reading education. There have been notable advances in the research of readability assessment following the advances of natural language processing techniques. Specifically, newer formulas make use of complex linguistic features that were previously unavailable, as well as contextually representative word-embeddings derived by training neural networks. However, there remain limitations for newer readability formulas, especially with respect to the employment of newer formulas by educational content creators. This paper provides an overview of readability research and introduces a new web app to help facilitate the application of state-of-the-art readability formulas for educational content creators and researchers through both an online interface and a separate API. An increase in accessibility and exposure for state-of-the-art readability formulas will assist in addressing many limitations of integrating readability research into educational technologies.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125551909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00120
Young Park
Quizzes, tests and exams are commonly used as important formative and summative assessment tools to test student learning towards learning objectives. Practice exams are an effective tool to help students better prepare for real exams in an in-person as well as online course environment. Personalized practice exams will be more effective for supporting individual students’ success in course assessments. In this paper, we present a personalized practice exam recommender system to help students prepare and do better in the real course exams. Our practice exam recommendation is based on the student-to-student collaborative filtering using course, exam and exam question grades. We compute a target student’s predicted grade on each exam question in a real exam, and based on the predicted grades, construct and recommend a personalized practice exam for the target student. Practice exam recommendation can be done at the beginning of a semester or progressively in course throughout a semester by incorporating the target student’s performance on the completed real exams.
{"title":"Personalized Practice Exam Recommendation for Helping Students Prepare for Course Assessment","authors":"Young Park","doi":"10.1109/ICALT55010.2022.00120","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00120","url":null,"abstract":"Quizzes, tests and exams are commonly used as important formative and summative assessment tools to test student learning towards learning objectives. Practice exams are an effective tool to help students better prepare for real exams in an in-person as well as online course environment. Personalized practice exams will be more effective for supporting individual students’ success in course assessments. In this paper, we present a personalized practice exam recommender system to help students prepare and do better in the real course exams. Our practice exam recommendation is based on the student-to-student collaborative filtering using course, exam and exam question grades. We compute a target student’s predicted grade on each exam question in a real exam, and based on the predicted grades, construct and recommend a personalized practice exam for the target student. Practice exam recommendation can be done at the beginning of a semester or progressively in course throughout a semester by incorporating the target student’s performance on the completed real exams.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128588389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00099
Benedikt Hensen, R. Klamma
Curricula at university and learning paths in self-regulated learning span a complex planning space that is difficult to visualize. Students need to plan their decisions ahead to take a valid order of courses that align with their learning goals. Previous approaches used 2D skill tree visualizations to map the dependencies which, however, cannot convey mixtures of long-term goals and short-term action plans well. We present an approach that realizes learning plans as 3D skill tree structures in mixed reality. With the extra dimension, clearer layouts can be found which combine views on long-term goals and specific actions. By bringing the 3D learning plans to mixed reality, depth perception can help the students to understand the 3D structure of the tree. Moreover, nodes of the tree can be anchored at places in the real world which aids the students’ spatial memory to help them remember the plan. The application is evaluated in two user studies with 17 and 53 participants, respectively. Although the amount of text and typing should be minimized, the results show that 3D learning plans are understood by students. As the hardware becomes more available, the 3D learning plans can help students to structure their studies.
{"title":"3D Skill Trees in Mixed Reality for Creating and Visualizing Learning Plans","authors":"Benedikt Hensen, R. Klamma","doi":"10.1109/ICALT55010.2022.00099","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00099","url":null,"abstract":"Curricula at university and learning paths in self-regulated learning span a complex planning space that is difficult to visualize. Students need to plan their decisions ahead to take a valid order of courses that align with their learning goals. Previous approaches used 2D skill tree visualizations to map the dependencies which, however, cannot convey mixtures of long-term goals and short-term action plans well. We present an approach that realizes learning plans as 3D skill tree structures in mixed reality. With the extra dimension, clearer layouts can be found which combine views on long-term goals and specific actions. By bringing the 3D learning plans to mixed reality, depth perception can help the students to understand the 3D structure of the tree. Moreover, nodes of the tree can be anchored at places in the real world which aids the students’ spatial memory to help them remember the plan. The application is evaluated in two user studies with 17 and 53 participants, respectively. Although the amount of text and typing should be minimized, the results show that 3D learning plans are understood by students. As the hardware becomes more available, the 3D learning plans can help students to structure their studies.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114828729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00110
Zhaoxin Feng, Chenxi Gong, Xinyue Jiao, Zifeng Liu, Su Cai
Preschool children have difficulty learning and comprehending abstract concepts, and the cognition of numbers has always been the key to mathematical enlightenment for young children. Our research aims to help preschool children build their cognition of cardinal and ordinal numbers, comprehend simple logical relationships, and master simple digital addition. We developed an Augmented Reality learning tool based on theories related to number cognition and a theoretical framework of software design for preschool children. We also conducted a teaching experiment in a kindergarten, and interviewed the teachers of the kindergarten to learn about their attitudes towards the application of AR in preschool education. Through data analysis, interviews, and discussions, we conclude that (a) AR application can positively influence children’s cognitive digital skills; (b) children have positive attitudes and positive evaluations toward AR application use, but there are some unavoidable problems in children’s attention allocation; (c) proficiency in operating AR tools has a large impact on children’s learning effects.
{"title":"The Effects of AR Learning Environment to Preschool Children’s Numerical Cognition","authors":"Zhaoxin Feng, Chenxi Gong, Xinyue Jiao, Zifeng Liu, Su Cai","doi":"10.1109/ICALT55010.2022.00110","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00110","url":null,"abstract":"Preschool children have difficulty learning and comprehending abstract concepts, and the cognition of numbers has always been the key to mathematical enlightenment for young children. Our research aims to help preschool children build their cognition of cardinal and ordinal numbers, comprehend simple logical relationships, and master simple digital addition. We developed an Augmented Reality learning tool based on theories related to number cognition and a theoretical framework of software design for preschool children. We also conducted a teaching experiment in a kindergarten, and interviewed the teachers of the kindergarten to learn about their attitudes towards the application of AR in preschool education. Through data analysis, interviews, and discussions, we conclude that (a) AR application can positively influence children’s cognitive digital skills; (b) children have positive attitudes and positive evaluations toward AR application use, but there are some unavoidable problems in children’s attention allocation; (c) proficiency in operating AR tools has a large impact on children’s learning effects.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124050625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00105
Antony Prakash, R. Rajendran
Virtual Reality (VR) has the potential to improve learning in the education domain due to its characteristics such as multi-sensory stimuli, immersion, interaction, first-person perspectives, etc. In spite of these advantages, the literature analysis carried out has revealed that there is no literature that explored the learning processes happening in a VR environment. The learning processes can be analyzed using the data collected from the interaction behavior happening in a VR learning environment (VRLE). The existing data collection mechanisms in VR such as questionnaires, surveys, physiological sensors, and human observers do not provide data related to the interaction behavior of the learners happening in VR head-mounted displays (HMD). Hence, in this paper, we discuss a mechanism developed to log the interaction data happening in VRLE automatically in real-time and store them in a locally accessible location. The logged interaction data can be further processed to extract features and study the learning processes in VRLE.
{"title":"Mechanism to Capture Learners’ Interactions in Virtual Reality Learning Environment","authors":"Antony Prakash, R. Rajendran","doi":"10.1109/ICALT55010.2022.00105","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00105","url":null,"abstract":"Virtual Reality (VR) has the potential to improve learning in the education domain due to its characteristics such as multi-sensory stimuli, immersion, interaction, first-person perspectives, etc. In spite of these advantages, the literature analysis carried out has revealed that there is no literature that explored the learning processes happening in a VR environment. The learning processes can be analyzed using the data collected from the interaction behavior happening in a VR learning environment (VRLE). The existing data collection mechanisms in VR such as questionnaires, surveys, physiological sensors, and human observers do not provide data related to the interaction behavior of the learners happening in VR head-mounted displays (HMD). Hence, in this paper, we discuss a mechanism developed to log the interaction data happening in VRLE automatically in real-time and store them in a locally accessible location. The logged interaction data can be further processed to extract features and study the learning processes in VRLE.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124150943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Learning Chinese Numeral-Classifier-Noun (NCN) phrases is one of the most challenging tasks for Chinese language learners. In this study, we developed learning applications based on a multimodal robot and IoT tangible objects (R&T) learning system to help Chinese language learners, adopting technologies suiting language learning, and implementing instructional design by professional Chinese language teachers. This study adopted the ASSURE model to develop and investigate the effect of the learning system and applications. Participants were divided into two groups: learning after a human teacher and learning with the R&T learning system. Findings from Table 1 show that learning Chinese NCN Phrases with the R&T learning system is comparable to the human teacher. This study contributes to Chinese language teaching and learning by providing an alternative method for Chinese language learners learning Chinese NCN phrases or a teaching assistant system for Chinese language teachers.
{"title":"An Innovative Multimodal Learning System Based on Robot and Tangible Objects for Chinese Numeral-Classifier-Noun Phrase Learning","authors":"Fu-Hui Hsu, Yu-Tang Hsueh, Wei-Lun Chang, Yen-Ting Lin, Y. Lan, Nian-Shing Chen","doi":"10.1109/ICALT55010.2022.00072","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00072","url":null,"abstract":"Learning Chinese Numeral-Classifier-Noun (NCN) phrases is one of the most challenging tasks for Chinese language learners. In this study, we developed learning applications based on a multimodal robot and IoT tangible objects (R&T) learning system to help Chinese language learners, adopting technologies suiting language learning, and implementing instructional design by professional Chinese language teachers. This study adopted the ASSURE model to develop and investigate the effect of the learning system and applications. Participants were divided into two groups: learning after a human teacher and learning with the R&T learning system. Findings from Table 1 show that learning Chinese NCN Phrases with the R&T learning system is comparable to the human teacher. This study contributes to Chinese language teaching and learning by providing an alternative method for Chinese language learners learning Chinese NCN phrases or a teaching assistant system for Chinese language teachers.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"37 24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125704541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00088
Jairo Quintero, S. Baldiris, Jhoni Cerón, Juan Garzón, D. Burgos, Gloria Liliana Velez Saldarriaga
Today’s education must offer multiple opportunities to address the individual needs of all students. In this context, educational innovation plays an important role in guiding the processes of creating strategies to achieve more inclusive learning and teaching. Many studies have analyzed the affordances of augmented reality, gamification, and the adoption of Universal Design for Learning as separate strategies to improve education. In turn, this paper presents the combination of these three strategies as a positive alternative to address diversity in the classroom. A gamified augmented educational application has been designed that considers the principles of Universal Design for Learning to teach robotics in secondary education. The results show the application facilitates the inclusion of students, improving the fulfillment of the academic challenges.
{"title":"Gamification as Support for Educational Inclusion: The Case of AR-mBot","authors":"Jairo Quintero, S. Baldiris, Jhoni Cerón, Juan Garzón, D. Burgos, Gloria Liliana Velez Saldarriaga","doi":"10.1109/ICALT55010.2022.00088","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00088","url":null,"abstract":"Today’s education must offer multiple opportunities to address the individual needs of all students. In this context, educational innovation plays an important role in guiding the processes of creating strategies to achieve more inclusive learning and teaching. Many studies have analyzed the affordances of augmented reality, gamification, and the adoption of Universal Design for Learning as separate strategies to improve education. In turn, this paper presents the combination of these three strategies as a positive alternative to address diversity in the classroom. A gamified augmented educational application has been designed that considers the principles of Universal Design for Learning to teach robotics in secondary education. The results show the application facilitates the inclusion of students, improving the fulfillment of the academic challenges.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130014790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00064
Ryoga Maruyama, M. Kayama, Takashi Nagai, Koki Otaku, Naomi Taguchi
This study aims to explore an educational learning environment that supports students to learn conceptual modeling with UML. In this study, we call the describing models “UML programming.” In this paper, we show an educational UML programming environment for STEAM-related subjects (for example, Technology or Engineering) in schools. The features of the proposed learning environment are 1) educational task management function and 2) models, which are created by students, management function.
{"title":"Proposal of a conceptual modeling learning environment with task/model management functions","authors":"Ryoga Maruyama, M. Kayama, Takashi Nagai, Koki Otaku, Naomi Taguchi","doi":"10.1109/ICALT55010.2022.00064","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00064","url":null,"abstract":"This study aims to explore an educational learning environment that supports students to learn conceptual modeling with UML. In this study, we call the describing models “UML programming.” In this paper, we show an educational UML programming environment for STEAM-related subjects (for example, Technology or Engineering) in schools. The features of the proposed learning environment are 1) educational task management function and 2) models, which are created by students, management function.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131625395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：