Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00046
Francisco Crespi, Ishari Amarasinghe, M. Vujovic, Davinia Hernández Leo
This study investigates the extent to which Electrodermal Activity (EDA) sensor data can be triangulated with self-perception measures to estimate facets of teachers’ orchestration load in the context of Computer-Supported Collaborative Learning (CSCL). It was expected to observe variances in the EDA signal as a result of stressful moments and incidents related to orchestration. Study findings indicated that EDA variations concurred with situations in which the teacher reported feeling stressed when orchestrating CSCL Pyramid scripts.
{"title":"Estimating Orchestration Load in CSCL Situations Using EDA","authors":"Francisco Crespi, Ishari Amarasinghe, M. Vujovic, Davinia Hernández Leo","doi":"10.1109/ICALT55010.2022.00046","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00046","url":null,"abstract":"This study investigates the extent to which Electrodermal Activity (EDA) sensor data can be triangulated with self-perception measures to estimate facets of teachers’ orchestration load in the context of Computer-Supported Collaborative Learning (CSCL). It was expected to observe variances in the EDA signal as a result of stressful moments and incidents related to orchestration. Study findings indicated that EDA variations concurred with situations in which the teacher reported feeling stressed when orchestrating CSCL Pyramid scripts.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"194 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":"122970079","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/ICALT55010.2022.00051
Yikai Lu, Teresa M. Ober, Cheng Liu, Ying Cheng
Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature extraction by neighborhood components analysis (NCA). Our dataset comprises 287 features from both process data indicators (i.e., derived from log data of an online statistics learning platform) and self-report data from high school students enrolled in Advanced Placement (AP) Statistics (N=733). As a label for prediction, we use students’ scores on the AP Statistics exam. We evaluated the performance of machine learning classifiers with a given feature extraction method by evaluation criteria including F1 scores, the area under the receiver operating characteristic curve (AUC), and Cohen’s Kappas. We find that NCA effectively reduces the dimensionality of training datasets, stabilizes machine learning predictions, and produces interpretable scores. However, interpreting the NCA weights of features, while feasible, is not very straightforward compared to linear regression. Future research should consider developing guidelines to interpret NCA weights.
{"title":"Application of Neighborhood Components Analysis to Process and Survey Data to Predict Student Learning of Statistics","authors":"Yikai Lu, Teresa M. Ober, Cheng Liu, Ying Cheng","doi":"10.1109/ICALT55010.2022.00051","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00051","url":null,"abstract":"Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature extraction by neighborhood components analysis (NCA). Our dataset comprises 287 features from both process data indicators (i.e., derived from log data of an online statistics learning platform) and self-report data from high school students enrolled in Advanced Placement (AP) Statistics (N=733). As a label for prediction, we use students’ scores on the AP Statistics exam. We evaluated the performance of machine learning classifiers with a given feature extraction method by evaluation criteria including F1 scores, the area under the receiver operating characteristic curve (AUC), and Cohen’s Kappas. We find that NCA effectively reduces the dimensionality of training datasets, stabilizes machine learning predictions, and produces interpretable scores. However, interpreting the NCA weights of features, while feasible, is not very straightforward compared to linear regression. Future research should consider developing guidelines to interpret NCA weights.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"103 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":"133557830","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/ICALT55010.2022.00115
Oscar Karnalim, Afifah Muharikah, Sunarto Natsir
Entering post-pandemic era, some countries consider combining online learning with onsite learning. Given that educators play an important role in the success of such combination, it is important to summarise their perspective about online learning and consider that in designing such combination. This quantitative study summarises perspective of 210 educators about that matter in Indonesia. In general, educators see benefits of online learning except in promoting educators’ teaching presence, supporting vulnerable students, and maintaining student integrity. These issues should be addressed first before combining online learning with onsite learning.
{"title":"Online Learning for High Quality Education: Perspective of Indonesian Educators","authors":"Oscar Karnalim, Afifah Muharikah, Sunarto Natsir","doi":"10.1109/ICALT55010.2022.00115","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00115","url":null,"abstract":"Entering post-pandemic era, some countries consider combining online learning with onsite learning. Given that educators play an important role in the success of such combination, it is important to summarise their perspective about online learning and consider that in designing such combination. This quantitative study summarises perspective of 210 educators about that matter in Indonesia. In general, educators see benefits of online learning except in promoting educators’ teaching presence, supporting vulnerable students, and maintaining student integrity. These issues should be addressed first before combining online learning with onsite learning.","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":"132730507","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/ICALT55010.2022.00012
Anuj Gopal
Artificial Intelligence has contributed remarkably towards educational purposes in the last few decades. With the rise of online learning, most of the tedious tasks have been transferred from the human hands to machines and programs. Question generation from educational paragraphs has been a challenging activity for educators as it requires significant resources. Although there have been major breakthroughs in the English language towards this goal, there is a need for technology-enabled educational services in Indian regional languages. In this paper, we present automatic question generation for two Indian languages - Hindi and Marathi utilizing Sentence Constituency Parsing with openAI Generative Pre-Trained(GPT) and Text-to-Text Transfer Transformers(T5) models, evaluated by content experts of corresponding languages, generating optimum questions after removing repetitions and inaccuracies in structural constraints on composition.
{"title":"Automatic Question Generation for Hindi and Marathi","authors":"Anuj Gopal","doi":"10.1109/ICALT55010.2022.00012","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00012","url":null,"abstract":"Artificial Intelligence has contributed remarkably towards educational purposes in the last few decades. With the rise of online learning, most of the tedious tasks have been transferred from the human hands to machines and programs. Question generation from educational paragraphs has been a challenging activity for educators as it requires significant resources. Although there have been major breakthroughs in the English language towards this goal, there is a need for technology-enabled educational services in Indian regional languages. In this paper, we present automatic question generation for two Indian languages - Hindi and Marathi utilizing Sentence Constituency Parsing with openAI Generative Pre-Trained(GPT) and Text-to-Text Transfer Transformers(T5) models, evaluated by content experts of corresponding languages, generating optimum questions after removing repetitions and inaccuracies in structural constraints on composition.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"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":"131872977","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/ICALT55010.2022.00048
K. Sharma, I. Pappas, Sofia Papavlasopoulou, M. Giannakos
The confluence of wearable technologies for sensing learners and the quantified-self provides a unique opportunity to understand learners’ experience in diverse learning contexts. We use data from learners using Empatica Wristbands and self-reported questionnaire. We compute stress, arousal, engagement and emotional regulation from physiological data; and perceived performance from the self-reported data. We use Fuzzy Set Qualitative Comparative Analysis (fsQCA) to find relations between the physiological measurements and the perceived learning performance. The results show how the presence or absence of arousal, engagement, emotional regulation, and stress, as well as their combinations, can be sufficient to explain high perceived learning performance
{"title":"Wearable Sensing and Quantified-self to explain Learning Experience","authors":"K. Sharma, I. Pappas, Sofia Papavlasopoulou, M. Giannakos","doi":"10.1109/ICALT55010.2022.00048","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00048","url":null,"abstract":"The confluence of wearable technologies for sensing learners and the quantified-self provides a unique opportunity to understand learners’ experience in diverse learning contexts. We use data from learners using Empatica Wristbands and self-reported questionnaire. We compute stress, arousal, engagement and emotional regulation from physiological data; and perceived performance from the self-reported data. We use Fuzzy Set Qualitative Comparative Analysis (fsQCA) to find relations between the physiological measurements and the perceived learning performance. The results show how the presence or absence of arousal, engagement, emotional regulation, and stress, as well as their combinations, can be sufficient to explain high perceived learning performance","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"9 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":"132035329","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/ICALT55010.2022.00127
Wayne J. Brown, Kinshuk
Hybrid simulation in Health Care education is primarily focused on simulations designed to emulate a specific medical scenario. This paper presents a theoretical framework for the implementation of a configurable hybrid simulation approach using advanced technologies and human actors. This approach would provide higher education institutions with a flexible approach to hybrid simulations that could be used across multiple faculties for a variety of scenarios.
{"title":"Improving simulation-based healthcare education through human actors, wearable, and web-based technology","authors":"Wayne J. Brown, Kinshuk","doi":"10.1109/ICALT55010.2022.00127","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00127","url":null,"abstract":"Hybrid simulation in Health Care education is primarily focused on simulations designed to emulate a specific medical scenario. This paper presents a theoretical framework for the implementation of a configurable hybrid simulation approach using advanced technologies and human actors. This approach would provide higher education institutions with a flexible approach to hybrid simulations that could be used across multiple faculties for a variety of scenarios.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"8 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":"130911545","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/ICALT55010.2022.00104
Maria Sounti, Caterina Antonopoulou, Penny Papageogopoulou, Dimitris Charitos, Louiza Katsarou, George Anastassakis
Due to the outbreak of COVID-19 pandemic, higher education institutes quickly turn to the use of online tools, radically transforming the modes of teaching and communication with students. This educational shift significantly affected the conduct of artistic laboratory courses, where physical presence is essential for students and teaching staff. In order to address this shift, the teaching staff for the laboratory course “Digital Artistic Creation 2”, of the Department of Digital Arts and Cinema of the National and Kapodistrian University of Athens adopted a project-based learning methodology and used a combination of teleconferencing tools and multiuser 3D Social Virtual Environments, to teach the creation of interactive and possibly dynamically evolving 3D assemblages and spatial compositions. This paper presents a research study which aims at investigating the result of this teaching course with regards to the educational impact and the experience of the students. The study was conducted at the end of the semester with the use of questionnaires delivered to the students in order to explore the learning experiences, outcomes and improvisation suggestions concerning this novel, combined form of teaching, as well as to detect the emerging collaborative and self-regulated learning patterns that emerged throughout the course.
{"title":"Investigating the Process of Teaching the Creation of Interactive Art in a Collaborative Virtual Environmental Context","authors":"Maria Sounti, Caterina Antonopoulou, Penny Papageogopoulou, Dimitris Charitos, Louiza Katsarou, George Anastassakis","doi":"10.1109/ICALT55010.2022.00104","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00104","url":null,"abstract":"Due to the outbreak of COVID-19 pandemic, higher education institutes quickly turn to the use of online tools, radically transforming the modes of teaching and communication with students. This educational shift significantly affected the conduct of artistic laboratory courses, where physical presence is essential for students and teaching staff. In order to address this shift, the teaching staff for the laboratory course “Digital Artistic Creation 2”, of the Department of Digital Arts and Cinema of the National and Kapodistrian University of Athens adopted a project-based learning methodology and used a combination of teleconferencing tools and multiuser 3D Social Virtual Environments, to teach the creation of interactive and possibly dynamically evolving 3D assemblages and spatial compositions. This paper presents a research study which aims at investigating the result of this teaching course with regards to the educational impact and the experience of the students. The study was conducted at the end of the semester with the use of questionnaires delivered to the students in order to explore the learning experiences, outcomes and improvisation suggestions concerning this novel, combined form of teaching, as well as to detect the emerging collaborative and self-regulated learning patterns that emerged throughout the course.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"1 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":"131368206","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/ICALT55010.2022.00020
Jim Goodell, M. Jay, Nkaepe E. E. Olaniyi, J. Rogers
This discussion paper presents learning engineering as an emerging new domain of engineering. It asks what role IEEE should play in establishing this branch of engineering in support of its mission to foster technological innovation and excellence for the benefit of humanity.
{"title":"Should IEEE Establish Learning Engineering as a New Engineering Profession?","authors":"Jim Goodell, M. Jay, Nkaepe E. E. Olaniyi, J. Rogers","doi":"10.1109/ICALT55010.2022.00020","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00020","url":null,"abstract":"This discussion paper presents learning engineering as an emerging new domain of engineering. It asks what role IEEE should play in establishing this branch of engineering in support of its mission to foster technological innovation and excellence for the benefit of humanity.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"37 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":"123752704","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/ICALT55010.2022.00128
J. K. Kristensen, Björn Andersson, J. V. K. Torkildsen
Disengagement from task content in educational apps may have a severe negative impact on learning outcomes. In the current study, we propose repeated mistakes as an indicator of disengaged guessing behavior that may be detrimental to learning. Furthermore, we propose a hierarchical generalized linear model to examine predictors of disengaged guessing behavior relating to student, item and session characteristics. Knowledge of how different characteristics contribute to the prediction of disengaged guessing may provide important information to teachers regarding which students are likely to engage in such behavior, as well as to app developers regarding the functioning of different types of task and session content.
{"title":"Modeling Disengaged Guessing Behavior in a Vocabulary Learning App using Student, Item, and Session Characteristics","authors":"J. K. Kristensen, Björn Andersson, J. V. K. Torkildsen","doi":"10.1109/ICALT55010.2022.00128","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00128","url":null,"abstract":"Disengagement from task content in educational apps may have a severe negative impact on learning outcomes. In the current study, we propose repeated mistakes as an indicator of disengaged guessing behavior that may be detrimental to learning. Furthermore, we propose a hierarchical generalized linear model to examine predictors of disengaged guessing behavior relating to student, item and session characteristics. Knowledge of how different characteristics contribute to the prediction of disengaged guessing may provide important information to teachers regarding which students are likely to engage in such behavior, as well as to app developers regarding the functioning of different types of task and session content.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"71 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":"122956969","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/ICALT55010.2022.00025
Florin Anghel, E. Popescu
Selecting an appropriate graduation project and supervisor is an important step for BSc and MSc students; a good compatibility between the student and the teacher, in terms of personality and supervisory style, contributes to enhanced achievement, engagement and well-being. Nevertheless, few approaches have been proposed in the literature to use these compatibility factors for providing student-teacher matching recommendations. In this context, we propose a system called Smart Project Allocation (SPA) which facilitates the supervisor selection process by providing personalized suggestions based on comprehensive student and teacher models (including personality, supervisory style and topics of interest). In addition, the platform provides a mechanism for automatic project allocation, which dynamically assigns projects to students in a more efficient, fair and transparent manner than the traditional manual approach.
{"title":"Dynamic Graduation Project Allocation Based on Student-Teacher Profile Compatibility","authors":"Florin Anghel, E. Popescu","doi":"10.1109/ICALT55010.2022.00025","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00025","url":null,"abstract":"Selecting an appropriate graduation project and supervisor is an important step for BSc and MSc students; a good compatibility between the student and the teacher, in terms of personality and supervisory style, contributes to enhanced achievement, engagement and well-being. Nevertheless, few approaches have been proposed in the literature to use these compatibility factors for providing student-teacher matching recommendations. In this context, we propose a system called Smart Project Allocation (SPA) which facilitates the supervisor selection process by providing personalized suggestions based on comprehensive student and teacher models (including personality, supervisory style and topics of interest). In addition, the platform provides a mechanism for automatic project allocation, which dynamically assigns projects to students in a more efficient, fair and transparent manner than the traditional manual approach.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"51 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":"121543568","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}
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