Pub Date : 2021-07-01DOI: 10.1109/ICALT52272.2021.00114
Dirk T. Tempelaar, B. Rienties, Quan Nguyen
Accurate and timely measurement of learning engagement is crucial for the application of precision education. At the same time, it is still a central research theme, both in the learning analytics community as in the broader area of educational research. 'Engagement is one of the hottest research topics in the field of educational psychology' is for a good reason the opening sentence of a recent special issue. In our contribution, we propose a holistic approach to the measurement of engagement by integrating data of behavioral type through traces of learning processes captured from log files into affective, behavioral, and cognitive measures of engagement collected with surveys and cognitive measures from assessments for and as learning. We apply this holistic approach in an empirical analysis of dispositional learning analytics. Starting from four different engagement profiles created by two-step clustering, we find that these profiles primarily differ in their timing of engagement with learning. Next, we develop regression-based prediction models that make clear that trace, survey, and assessment data have complementary roles in signaling students at risk for failure and are all three crucial constituents of prediction equations that differ in the timing of learning feedback.
{"title":"Enabling Precision Education by Learning Analytics Applying Trace, Survey and Assessment Data","authors":"Dirk T. Tempelaar, B. Rienties, Quan Nguyen","doi":"10.1109/ICALT52272.2021.00114","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00114","url":null,"abstract":"Accurate and timely measurement of learning engagement is crucial for the application of precision education. At the same time, it is still a central research theme, both in the learning analytics community as in the broader area of educational research. 'Engagement is one of the hottest research topics in the field of educational psychology' is for a good reason the opening sentence of a recent special issue. In our contribution, we propose a holistic approach to the measurement of engagement by integrating data of behavioral type through traces of learning processes captured from log files into affective, behavioral, and cognitive measures of engagement collected with surveys and cognitive measures from assessments for and as learning. We apply this holistic approach in an empirical analysis of dispositional learning analytics. Starting from four different engagement profiles created by two-step clustering, we find that these profiles primarily differ in their timing of engagement with learning. Next, we develop regression-based prediction models that make clear that trace, survey, and assessment data have complementary roles in signaling students at risk for failure and are all three crucial constituents of prediction equations that differ in the timing of learning feedback.","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":"124435713","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/ICALT52272.2021.00089
Hsuang-Yu Li
This study provides the designing of the empowering training model of robot-assisted language learning (RALL) knowledge based on the framework of Technological Pedagogical Content Knowledge (TPACK) for Chinese as a Second Language (CSL) teacher. The model is a 10-hours program to enhance CSL teachers’ cognition of robot technology knowledge, and integrate Chinese pedagogical knowledge and Chinese phonetics knowledge. We analyzed what should be included in TK, PK, CK, TPK, TCK, PCK, TPACK when designing a robot assisted Chinese phonetics teaching. Also, computational thinking and Chinese teaching-oriented programming is been taught in order to let the CSL teachers have the ability to realize their design of RALL system.
{"title":"The Designing of CSL Teacher Empowering Training Model of Robot-Assisted Language Learning based on the TPACK Framework","authors":"Hsuang-Yu Li","doi":"10.1109/ICALT52272.2021.00089","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00089","url":null,"abstract":"This study provides the designing of the empowering training model of robot-assisted language learning (RALL) knowledge based on the framework of Technological Pedagogical Content Knowledge (TPACK) for Chinese as a Second Language (CSL) teacher. The model is a 10-hours program to enhance CSL teachers’ cognition of robot technology knowledge, and integrate Chinese pedagogical knowledge and Chinese phonetics knowledge. We analyzed what should be included in TK, PK, CK, TPK, TCK, PCK, TPACK when designing a robot assisted Chinese phonetics teaching. Also, computational thinking and Chinese teaching-oriented programming is been taught in order to let the CSL teachers have the ability to realize their design of RALL system.","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":"116686022","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/ICALT52272.2021.00058
Xi Zhao, Jingjing Zhang, Wenshuo Li, Ken Kahn, Yu Lu, N. Winters
The interest in artificial intelligence (AI) education is growing exponentially; nevertheless, how to learn about AI, particularly Natural Language Processing (NLP), has been a challenging problem for educators and researchers worldwide. This study used a graphical programming platform Snap! to facilitate learning by allowing learners to explore AI and its NLP techniques in class. Data from 18,452 logged events were collected and Lag Sequential Analysis (LSA) was used to examine how learners behaved and learned sequentially. Non-cognitive factors were used to group learners as detailed and subtle behavior sequences that did not occur by chance could be uncovered. The results showed that five groups of learners, that is Passive Learners, Performers, Adaptive Learners, Interested Learners, and Dedicated Learners. They presented varied learning behavior patterns, which should be considered further in designing personalized and intelligent learning platforms to support AI education.
{"title":"Learners’ non-cognitive skills and behavioral patterns of programming: A sequential analysis","authors":"Xi Zhao, Jingjing Zhang, Wenshuo Li, Ken Kahn, Yu Lu, N. Winters","doi":"10.1109/ICALT52272.2021.00058","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00058","url":null,"abstract":"The interest in artificial intelligence (AI) education is growing exponentially; nevertheless, how to learn about AI, particularly Natural Language Processing (NLP), has been a challenging problem for educators and researchers worldwide. This study used a graphical programming platform Snap! to facilitate learning by allowing learners to explore AI and its NLP techniques in class. Data from 18,452 logged events were collected and Lag Sequential Analysis (LSA) was used to examine how learners behaved and learned sequentially. Non-cognitive factors were used to group learners as detailed and subtle behavior sequences that did not occur by chance could be uncovered. The results showed that five groups of learners, that is Passive Learners, Performers, Adaptive Learners, Interested Learners, and Dedicated Learners. They presented varied learning behavior patterns, which should be considered further in designing personalized and intelligent learning platforms to support AI 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":"121282676","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/ICALT52272.2021.00066
Afaf Ahmed, I. Zualkernan, H. Elghazaly
Online learning platforms are generating an enormous amount of data that lends itself to unsupervised learning. This paper presents a case study where assessment data from two online platforms was used to cluster students into similar groups. The long-term objective of this research is to incorporate the clustering information into the personalization mechanisms. K-means was used to cluster students for 10 Skills. K-means was able to create a small number of clusters with reasonable internal validity with an average silhouette width of 0.32 (sd=0.05). The clusters were non-trivial as gender, school or class could not explain the clustering with an average Adjusted Rand Index (ARI) of 0.049 (sd=0.03). Most importantly, only a small subset (18%) of attempted questions could be used to explain accurately (Average F1-measure = 89.43) why the students were grouped into clusters. These keystone questions can be used to further enhance the personalization mechanisms.
{"title":"Unsupervised Clustering of Skills for an Online Learning Platform","authors":"Afaf Ahmed, I. Zualkernan, H. Elghazaly","doi":"10.1109/ICALT52272.2021.00066","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00066","url":null,"abstract":"Online learning platforms are generating an enormous amount of data that lends itself to unsupervised learning. This paper presents a case study where assessment data from two online platforms was used to cluster students into similar groups. The long-term objective of this research is to incorporate the clustering information into the personalization mechanisms. K-means was used to cluster students for 10 Skills. K-means was able to create a small number of clusters with reasonable internal validity with an average silhouette width of 0.32 (sd=0.05). The clusters were non-trivial as gender, school or class could not explain the clustering with an average Adjusted Rand Index (ARI) of 0.049 (sd=0.03). Most importantly, only a small subset (18%) of attempted questions could be used to explain accurately (Average F1-measure = 89.43) why the students were grouped into clusters. These keystone questions can be used to further enhance the personalization mechanisms.","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":"127439251","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/ICALT52272.2021.00127
G. Resch, Joseph X Manzone, T. Welsh, Michael Nitsche, Ali Mazalek
Multi-modal technologies, including augmented reality (AR) and virtual reality (VR), have become increasingly common in education and training contexts. Despite growing adoption of these technologies, our understanding of how basic perceptual-cognitive processes are influenced or altered by AR and VR mediation remains limited. The present paper describes a pilot study in which participants performed goal-directed reaching movements toward visual illusions in three different mediation conditions: unmediated reality (UR), AR, and VR. This pilot assessed whether the speed-accuracy relationship of reaching movements in different mediation conditions was modulated by contextual information surrounding a target. Preliminary results showed that there was a trend toward an effect of the contextual information in VR, but not in UR or AR. These findings may indicate that movements in VR are generated by different sensorimotor processes than in UR and AR.
{"title":"Goal-Directed Reaching in Real, Augmented, and Virtual Environments","authors":"G. Resch, Joseph X Manzone, T. Welsh, Michael Nitsche, Ali Mazalek","doi":"10.1109/ICALT52272.2021.00127","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00127","url":null,"abstract":"Multi-modal technologies, including augmented reality (AR) and virtual reality (VR), have become increasingly common in education and training contexts. Despite growing adoption of these technologies, our understanding of how basic perceptual-cognitive processes are influenced or altered by AR and VR mediation remains limited. The present paper describes a pilot study in which participants performed goal-directed reaching movements toward visual illusions in three different mediation conditions: unmediated reality (UR), AR, and VR. This pilot assessed whether the speed-accuracy relationship of reaching movements in different mediation conditions was modulated by contextual information surrounding a target. Preliminary results showed that there was a trend toward an effect of the contextual information in VR, but not in UR or AR. These findings may indicate that movements in VR are generated by different sensorimotor processes than in UR and AR.","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":"127516250","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/ICALT52272.2021.00039
Lan Wu, Yang Liu, Axi Wang, YuanLi Gong, Shengquan Yu
Collaborative problem solving (CPS) is a key skill for the success in education and workforce. The CPS performance is determined by the interaction of problem solving process and collaboration. Thus, the interaction of cognitive and social aspects should be included in the CPS assessment. This study presented a method to analyze the interaction through extending the coding framework from the Assessment and Teaching of 21st Century Skills (ATC21S) project. The results showed that the high task performance group outperformed the low one in terms of the interactive chat-action pattern and participation pattern. Besides, a visual representation of the participation pattern exhibited more details about the interaction.
{"title":"An analysis of Interaction of Cognitive and Social Aspects during Collaborative Problem Solving","authors":"Lan Wu, Yang Liu, Axi Wang, YuanLi Gong, Shengquan Yu","doi":"10.1109/ICALT52272.2021.00039","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00039","url":null,"abstract":"Collaborative problem solving (CPS) is a key skill for the success in education and workforce. The CPS performance is determined by the interaction of problem solving process and collaboration. Thus, the interaction of cognitive and social aspects should be included in the CPS assessment. This study presented a method to analyze the interaction through extending the coding framework from the Assessment and Teaching of 21st Century Skills (ATC21S) project. The results showed that the high task performance group outperformed the low one in terms of the interactive chat-action pattern and participation pattern. Besides, a visual representation of the participation pattern exhibited more details about the interaction.","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":"128559473","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/ICALT52272.2021.00077
D. Aranda, Alden Towler, Ramyaa, R. Kuo
Propositional logic is a fundamental concept in Computer Science. However, some students are struggling with connecting natural language statements and propositional logic. This research designs an escape room computer game that requires players to interpret the logic statements to escape the room. This paper presents a pilot user study to test the usability of the environment. This study shows that students believe the game is a good environment for learning. Moreover, students who like or dislike playing computer games give the same score in system usability, showing that students’ attitudes toward computer games does not affect their given score in system usability.
{"title":"The Usability of Using Educational Game for Teaching Foundational Concept in Propositional Logic","authors":"D. Aranda, Alden Towler, Ramyaa, R. Kuo","doi":"10.1109/ICALT52272.2021.00077","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00077","url":null,"abstract":"Propositional logic is a fundamental concept in Computer Science. However, some students are struggling with connecting natural language statements and propositional logic. This research designs an escape room computer game that requires players to interpret the logic statements to escape the room. This paper presents a pilot user study to test the usability of the environment. This study shows that students believe the game is a good environment for learning. Moreover, students who like or dislike playing computer games give the same score in system usability, showing that students’ attitudes toward computer games does not affect their given score in system usability.","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":"125479444","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/ICALT52272.2021.00099
Spruha Satavlekar, Debarshi Nath, R. Priyadarshini, Prajish Prasad, D. Singh, R. Rajendran
In the past, unraveling learner interaction data in TELE was a challenge. However, the advent of LA has helped in uncovering latent information in log data to scaffold learning. This paper focuses on learner interaction in VeriSIM, a TELE, to teach software design diagrams. The learners’ performance in the system is used to categorize them into three groups, namely, "full scorers", "partial scorers", and "give uppers". Our analysis found that the full scorers spend a significantly higher duration per action than the give-uppers in an introductory challenge presented in the learning environment. Further analysis unravels the strategies used by consistent and inconsistent learners, and it was observed that the learner interaction strategies evolve with increasing difficulty levels as they navigate through the challenges.
{"title":"Unraveling Learner Interaction Strategies in VeriSIM for Software Design Diagrams","authors":"Spruha Satavlekar, Debarshi Nath, R. Priyadarshini, Prajish Prasad, D. Singh, R. Rajendran","doi":"10.1109/ICALT52272.2021.00099","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00099","url":null,"abstract":"In the past, unraveling learner interaction data in TELE was a challenge. However, the advent of LA has helped in uncovering latent information in log data to scaffold learning. This paper focuses on learner interaction in VeriSIM, a TELE, to teach software design diagrams. The learners’ performance in the system is used to categorize them into three groups, namely, \"full scorers\", \"partial scorers\", and \"give uppers\". Our analysis found that the full scorers spend a significantly higher duration per action than the give-uppers in an introductory challenge presented in the learning environment. Further analysis unravels the strategies used by consistent and inconsistent learners, and it was observed that the learner interaction strategies evolve with increasing difficulty levels as they navigate through the challenges.","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":"121734232","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/ICALT52272.2021.00100
Jairo Quintero, S. Baldiris, Jhoni Cerón, Juan Garzón, D. Burgos, Gloria Liliana Velez Saldarriaga
Augmented reality (AR) is an emerging technology that has been successfully integrated into education. However, the use of AR as a tool to achieve educational inclusion has not been deeply explored. This study introduces CooperAR, a methodology aimed at attending educational inclusion, understanding inclusion as a process where the needs of all students are taken into consideration. CooperAR focuses on the creation of AR-based learning scenarios, in which teachers and students become co-creators of content. The methodology is based on the principles of Universal Design for learning and the Cooperative Learning approach. The effectiveness of CooperAR was validated in the context of a case study that involved 66 students. The results showed promising results, suggesting that CooperAR is an efficient methodology to promote educational inclusion through cooperation.
{"title":"CooperAR: promoting educational inclusion through augmented reality","authors":"Jairo Quintero, S. Baldiris, Jhoni Cerón, Juan Garzón, D. Burgos, Gloria Liliana Velez Saldarriaga","doi":"10.1109/ICALT52272.2021.00100","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00100","url":null,"abstract":"Augmented reality (AR) is an emerging technology that has been successfully integrated into education. However, the use of AR as a tool to achieve educational inclusion has not been deeply explored. This study introduces CooperAR, a methodology aimed at attending educational inclusion, understanding inclusion as a process where the needs of all students are taken into consideration. CooperAR focuses on the creation of AR-based learning scenarios, in which teachers and students become co-creators of content. The methodology is based on the principles of Universal Design for learning and the Cooperative Learning approach. The effectiveness of CooperAR was validated in the context of a case study that involved 66 students. The results showed promising results, suggesting that CooperAR is an efficient methodology to promote educational inclusion through cooperation.","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":"130018368","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/ICALT52272.2021.00053
Negar Shabihi, Mi Song Kim
In the past decade, the applications of big data and learning analytics in education have made significant headways resulting in new opportunities for educational research. However, big data analytics (BDA) has brought new challenges to educational analytics. This paper conducts a systematic data-driven Literature review of BDA in education. Using a topic modeling approach, we have identified six topics and 19 subtopics and performed a network analysis to explore the links between the topics. Based on the results, we investigate the challenges in the field and conclude a three-dimensional model for educational BDA to address these challenges.
{"title":"Big Data Analytics in Education: A Data-Driven Literature Review","authors":"Negar Shabihi, Mi Song Kim","doi":"10.1109/ICALT52272.2021.00053","DOIUrl":"https://doi.org/10.1109/ICALT52272.2021.00053","url":null,"abstract":"In the past decade, the applications of big data and learning analytics in education have made significant headways resulting in new opportunities for educational research. However, big data analytics (BDA) has brought new challenges to educational analytics. This paper conducts a systematic data-driven Literature review of BDA in education. Using a topic modeling approach, we have identified six topics and 19 subtopics and performed a network analysis to explore the links between the topics. Based on the results, we investigate the challenges in the field and conclude a three-dimensional model for educational BDA to address these challenges.","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":"132984414","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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