The purposes of this study were to, first, design a holographic projection system to assist students in learning the concept of lunar phases. This study also aimed to evaluate university students’ learning achievements and self-efficacy after using this holographic projection system. A holographic projection system with three modes was developed. The system allows users to switch the modes and operate the system through the keyboard. 30 Taiwanese university students participated in a holographic projection learning activity. The participants’ knowledge acquisition and self-efficacy regarding lunar phases were evaluated through a pre-test and a post-test comparison. The results indicated that the participants showed significantly better learning achievements and higher self-efficacy after using the system. The findings of this study were expected to provide significant insights into how to adequately accommodate this novel technology in education.
{"title":"Development of a lunar-phase learning system based on holographic projection technology","authors":"Yang-Hsin Fan, Tzung-Jin Lin, Liang-Yi Li, Yu-Jou Chang","doi":"10.1109/ICALT52272.2021.00123","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00123","url":null,"abstract":"The purposes of this study were to, first, design a holographic projection system to assist students in learning the concept of lunar phases. This study also aimed to evaluate university students’ learning achievements and self-efficacy after using this holographic projection system. A holographic projection system with three modes was developed. The system allows users to switch the modes and operate the system through the keyboard. 30 Taiwanese university students participated in a holographic projection learning activity. The participants’ knowledge acquisition and self-efficacy regarding lunar phases were evaluated through a pre-test and a post-test comparison. The results indicated that the participants showed significantly better learning achievements and higher self-efficacy after using the system. The findings of this study were expected to provide significant insights into how to adequately accommodate this novel technology in education.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125047515","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00050
Thomas Sergent, Morgane Daniel, François Bouchet, T. Carron
The ability to self-regulate one’s learning (SRL) is considered to have a significant impact on educational outcomes. We present here a research work aiming first at detecting self-evaluation and self-efficacy deficits for young (5-7 years old) students, in the context of a literacy web application. From SRL answers we were able to characterize some answer patterns associated to SRL deficits, showing that around 30% of students seem to suffer from at least one of the four deficits considered in this study. We also surveyed close to 300 teachers to find out how they would like to be informed about their students’ SRL deficits and how they would address them, so that the remediation of deficits in the application could be co-designed with them.
{"title":"Addressing Children’s Self-Evaluation and Self-Efficacy Deficits in a Literacy Application","authors":"Thomas Sergent, Morgane Daniel, François Bouchet, T. Carron","doi":"10.1109/ICALT52272.2021.00050","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00050","url":null,"abstract":"The ability to self-regulate one’s learning (SRL) is considered to have a significant impact on educational outcomes. We present here a research work aiming first at detecting self-evaluation and self-efficacy deficits for young (5-7 years old) students, in the context of a literacy web application. From SRL answers we were able to characterize some answer patterns associated to SRL deficits, showing that around 30% of students seem to suffer from at least one of the four deficits considered in this study. We also surveyed close to 300 teachers to find out how they would like to be informed about their students’ SRL deficits and how they would address them, so that the remediation of deficits in the application could be co-designed with them.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122075271","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00009
David Roldán-álvarez, F. Martínez-Martínez, Estefanía Martín
Citizen science involves volunteers who participate in scientific research by collecting data or by addressing the needs of the project they are involved in. Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of research. Social networks, such as Twitter, are increasingly being investigated to capture online interactive participation, to be said, the degree of engagement of citizen science researchers with their projects. Although citizen science projects have been remarkably successful in advancing scientific knowledge, there is not really any evidence supporting that social networks act as learning tools and it is not even known whether the educational aspect is taken into account in citizen science projects. In this paper, we present a preliminary Twitter study where we analyse the conversation around education in the citizen science area. Although the results show that there is some talk around educational aspects, Twitter is not mainly used to support educational activities overall.
{"title":"Citizen Science and Open Learning: A Twitter perspective","authors":"David Roldán-álvarez, F. Martínez-Martínez, Estefanía Martín","doi":"10.1109/ICALT52272.2021.00009","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00009","url":null,"abstract":"Citizen science involves volunteers who participate in scientific research by collecting data or by addressing the needs of the project they are involved in. Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of research. Social networks, such as Twitter, are increasingly being investigated to capture online interactive participation, to be said, the degree of engagement of citizen science researchers with their projects. Although citizen science projects have been remarkably successful in advancing scientific knowledge, there is not really any evidence supporting that social networks act as learning tools and it is not even known whether the educational aspect is taken into account in citizen science projects. In this paper, we present a preliminary Twitter study where we analyse the conversation around education in the citizen science area. Although the results show that there is some talk around educational aspects, Twitter is not mainly used to support educational activities overall.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124012220","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00111
Cheng-Yo Huang-Fu, Chen-Hsuan Liao, Jiun-Yu Wu
The use of computer-mediated communication (CMC) has been ubiquitous in higher education. To better understand students’ behaviors and facilitate students’ learning through CMC, this study aimed to classify messages in Facebook learning group which was created as an on-line discussion board. Different machine learning and deep learning classification models were proposed, trained and testified with corpuses from PTT, one of the famous on-line forums in Taiwan. Furthermore, the classification of Facebook messages by these well-trained models were compared with human coding. Results revealed that recurrent neural network (RNN) with word to vector (W2V) for feature extraction demonstrated the best performance in accuracy. In addition, the combination of RNN and TF-IDF was proved to have the highest correlation with human work. Implications for artificial intelligence (AI) in education context was discussed.
{"title":"Comparing the performance of machine learning and deep learning algorithms classifying messages in Facebook learning group","authors":"Cheng-Yo Huang-Fu, Chen-Hsuan Liao, Jiun-Yu Wu","doi":"10.1109/ICALT52272.2021.00111","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00111","url":null,"abstract":"The use of computer-mediated communication (CMC) has been ubiquitous in higher education. To better understand students’ behaviors and facilitate students’ learning through CMC, this study aimed to classify messages in Facebook learning group which was created as an on-line discussion board. Different machine learning and deep learning classification models were proposed, trained and testified with corpuses from PTT, one of the famous on-line forums in Taiwan. Furthermore, the classification of Facebook messages by these well-trained models were compared with human coding. Results revealed that recurrent neural network (RNN) with word to vector (W2V) for feature extraction demonstrated the best performance in accuracy. In addition, the combination of RNN and TF-IDF was proved to have the highest correlation with human work. Implications for artificial intelligence (AI) in education context was discussed.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126046208","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00087
Fan Su, D. Zou
Within the Toulmin model of argumentative structure, this study examined collaboration approaches through Shimo-based co-argumentative writing of students in the student-picked groups and teacher-assigned groups. Students were fourth-year university students majoring in English. The differences between the two groups of students were analyzed, with seven collaboration approaches being identified. Additionally, students in the student-picked groups were more collaborative than the counterparts in the teacher-assigned groups. Discussions were expanded around this result.
{"title":"Shimo-based collaborative argumentative writing: Do grouping patterns matter?","authors":"Fan Su, D. Zou","doi":"10.1109/ICALT52272.2021.00087","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00087","url":null,"abstract":"Within the Toulmin model of argumentative structure, this study examined collaboration approaches through Shimo-based co-argumentative writing of students in the student-picked groups and teacher-assigned groups. Students were fourth-year university students majoring in English. The differences between the two groups of students were analyzed, with seven collaboration approaches being identified. Additionally, students in the student-picked groups were more collaborative than the counterparts in the teacher-assigned groups. Discussions were expanded around this result.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128272671","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00062
Dirk Ifenthaler, Clara Schumacher, Muhittin Şahin
Feedback has been identified as the most powerful moderator for supporting learning. Learning analytics haven been recognized for opportunities for providing timely and informative feedback to learners when they need it. This study seeks to investigate learners’ perceptions and expected benefits of different forms of learning analytics feedback from different sources. In a quasi-experimental study including 230 students, four experimental groups were confronted with five learning scenarios receiving different learning analytics feedback. Findings indicate that perceived benefits from learning analytics feedback varies across different delivery sources and requires informative recommendations. Accordingly, designing and implementing feedback in learning analytics systems is more complex than just providing visualizations of behavioral data.
{"title":"System-based or Teacher-based Learning Analytics Feedback – What Works Best?","authors":"Dirk Ifenthaler, Clara Schumacher, Muhittin Şahin","doi":"10.1109/ICALT52272.2021.00062","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00062","url":null,"abstract":"Feedback has been identified as the most powerful moderator for supporting learning. Learning analytics haven been recognized for opportunities for providing timely and informative feedback to learners when they need it. This study seeks to investigate learners’ perceptions and expected benefits of different forms of learning analytics feedback from different sources. In a quasi-experimental study including 230 students, four experimental groups were confronted with five learning scenarios receiving different learning analytics feedback. Findings indicate that perceived benefits from learning analytics feedback varies across different delivery sources and requires informative recommendations. Accordingly, designing and implementing feedback in learning analytics systems is more complex than just providing visualizations of behavioral data.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122487643","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 : 2021-07-01DOI: 10.1109/laclo.2016.7751740
Nian-Shing Chen
Local Organising Committee Emanuele Bardone, University of Tartu, Estonia Mirjam Burget, University of Tartu, Estonia Airi Heinaru, University of Tartu, Estonia Danial Hooshyar, University of Tartu, Estonia Sander Juss, University of Tartu, Estonia Meriliis Kasemets, University of Tartu, Estonia Margus Pedaste, University of Tartu, Estonia Katrin Saks, University of Tartu, Estonia Kristjan Roogsoo, University of Tartu, Estonia Eda Tagamets, University of Tartu, Estonia Kiiri Toomberg, University of Tartu, Estonia
{"title":"List of Chairs and PC Members","authors":"Nian-Shing Chen","doi":"10.1109/laclo.2016.7751740","DOIUrl":"https://doi.org/10.1109/laclo.2016.7751740","url":null,"abstract":"Local Organising Committee Emanuele Bardone, University of Tartu, Estonia Mirjam Burget, University of Tartu, Estonia Airi Heinaru, University of Tartu, Estonia Danial Hooshyar, University of Tartu, Estonia Sander Juss, University of Tartu, Estonia Meriliis Kasemets, University of Tartu, Estonia Margus Pedaste, University of Tartu, Estonia Katrin Saks, University of Tartu, Estonia Kristjan Roogsoo, University of Tartu, Estonia Eda Tagamets, University of Tartu, Estonia Kiiri Toomberg, University of Tartu, Estonia","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122820330","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00069
Siddharth Srivastava, T. Prabhakar
The micro-prompt* strategy balances several complex pedagogical tradeoffs hence found helpful in designing assignment free micro-lectures (MIL). Manual implementation of this strategy is time-consuming and may introduce human errors. This research is the answer to these problems. This research presents a desktop application entitled "AutoPrompt". This application helps in designing assignment free micro-lectures using the micro-prompt strategy by automating the MIL design process. The complete reference architecture of the proposed application is discussed in detail in this paper. To judge our application’s quality, we conducted a software testing program and found satisfying results, including some precious feedback. The details of the testing program, results and feedbacks are also presented in this paper. We believe that the reference architecture proposed in this paper helps researchers and software developers to design more sophisticated applications for online educators and learners.
{"title":"AutoPrompt: A Desktop Application for Designing Micro-Lectures using Micro-Prompt Strategy for Online Education Systems","authors":"Siddharth Srivastava, T. Prabhakar","doi":"10.1109/ICALT52272.2021.00069","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00069","url":null,"abstract":"The micro-prompt* strategy balances several complex pedagogical tradeoffs hence found helpful in designing assignment free micro-lectures (MIL). Manual implementation of this strategy is time-consuming and may introduce human errors. This research is the answer to these problems. This research presents a desktop application entitled \"AutoPrompt\". This application helps in designing assignment free micro-lectures using the micro-prompt strategy by automating the MIL design process. The complete reference architecture of the proposed application is discussed in detail in this paper. To judge our application’s quality, we conducted a software testing program and found satisfying results, including some precious feedback. The details of the testing program, results and feedbacks are also presented in this paper. We believe that the reference architecture proposed in this paper helps researchers and software developers to design more sophisticated applications for online educators and learners.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121490405","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00046
Clifton Kussmaul, Tammy Pirmann
Technology has the potential to improve the quality and scalability of education. Guided Inquiry Learning with Technology (GILT) studies how web-based collaborative tools can support Process Oriented Guided Inquiry Learning (POGIL) and other forms of social constructivism. This paper describes data visualization features to help instructors monitor the progress of student teams and facilitate learning, through the use of summary tables, timelines, Sankey diagrams, and word trees.
{"title":"Monitoring Student Team Progress and Responses in Guided Inquiry Learning with Technology","authors":"Clifton Kussmaul, Tammy Pirmann","doi":"10.1109/ICALT52272.2021.00046","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00046","url":null,"abstract":"Technology has the potential to improve the quality and scalability of education. Guided Inquiry Learning with Technology (GILT) studies how web-based collaborative tools can support Process Oriented Guided Inquiry Learning (POGIL) and other forms of social constructivism. This paper describes data visualization features to help instructors monitor the progress of student teams and facilitate learning, through the use of summary tables, timelines, Sankey diagrams, and word trees.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131021657","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 : 2021-07-01DOI: 10.1109/ICALT52272.2021.00131
Bihao Hu, Y. Liu, X. Gu
The purpose of this research was to explore how learners' non-cognitive abilities (including attention, engagement, presence, curiosity) differ in the learning process and the final learning results in VR and non-VR learning environments. This can be used to explain how the learning process of the learner in the VR environment occurs and changes, and the impact of the VR learning environment on the learner's non-cognitive ability. At the same time, it provided suggestions for the wider application of VR in education and the further development of personalized learning in education. Therefore, this research identified two research questions. The first one was whether the learning results of learners were different in VR and non-VR learning environments. The second was through the description of multimodal data such as eye movements and GSR. What was the relationship between the learner's non-cognitive abilities (attention, presence, engagement) and learning outcomes during the learning process? This study measured the curiosity of learners using a questionnaire before the experiment and measured the presence and engagement, compared scores between experimental group's and control groups' to understand how is immersed environment learning.
{"title":"Is it true that \"If you are not immersed, you are not learning\" where we will be?","authors":"Bihao Hu, Y. Liu, X. Gu","doi":"10.1109/ICALT52272.2021.00131","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00131","url":null,"abstract":"The purpose of this research was to explore how learners' non-cognitive abilities (including attention, engagement, presence, curiosity) differ in the learning process and the final learning results in VR and non-VR learning environments. This can be used to explain how the learning process of the learner in the VR environment occurs and changes, and the impact of the VR learning environment on the learner's non-cognitive ability. At the same time, it provided suggestions for the wider application of VR in education and the further development of personalized learning in education. Therefore, this research identified two research questions. The first one was whether the learning results of learners were different in VR and non-VR learning environments. The second was through the description of multimodal data such as eye movements and GSR. What was the relationship between the learner's non-cognitive abilities (attention, presence, engagement) and learning outcomes during the learning process? This study measured the curiosity of learners using a questionnaire before the experiment and measured the presence and engagement, compared scores between experimental group's and control groups' to understand how is immersed environment learning.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133481555","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：