International Journal of Artificial Intelligence in Education最新文献_第9页

Three Algorithms for Grouping Students: A Bridge Between Personalized Tutoring System Data and Classroom Pedagogy 学生分组的三种算法:个性化教学系统数据与课堂教学之间的桥梁

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-09-12 DOI: 10.1007/s40593-022-00309-y

Christopher G. Lechuga, Shayan Doroudi

引用次数: 1

Can Multi-Label Classifiers Help Identify Subjectivity? A Deep Learning Approach to Classifying Cognitive Presence in MOOCs. 多标签分类器能否帮助识别主观性？对 MOOC 中的认知存在进行分类的深度学习方法。

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-09-02 DOI: 10.1007/s40593-022-00310-5

Yuanyuan Hu, Claire Donald, Nasser Giacaman

{"title":"Can Multi-Label Classifiers Help Identify Subjectivity? A Deep Learning Approach to Classifying Cognitive Presence in MOOCs.","authors":"Yuanyuan Hu, Claire Donald, Nasser Giacaman","doi":"10.1007/s40593-022-00310-5","DOIUrl":"10.1007/s40593-022-00310-5","url":null,"abstract":"This paper investigates using multi-label deep learning approach to extending the understanding of cognitive presence in MOOC discussions. Previous studies demonstrate the challenges of subjectivity in manual categorisation methods. Training automatic single-label classifiers may preserve this subjectivity. Using a triangulation approach, we developed a multi-label, fine-tuning BERT classifier to analyse cognitive presence to enrich results with state-of-the-art, single-label classifiers. We trained the multi-label classifiers on the MOOC discussion messages that were categorised into the same phase of cognitive presence by the expert coders, and tested the best-performing classifiers on the messages that the coders categorised into different phases. The results suggest that multi-label classifiers slightly outperformed the single-label classifiers, and the multi-label classifiers predicted the discussion messages as either one category or two adjacent categories of cognitive presence. No messages were tagged as non-adjacent categories by the multi-label classifier. This is an improvement compared to manual categorisation by our expert coders, who obtained non-adjacent categories and even three categories of cognitive presence in one message. In addition to the fully correct prediction, parts of messages were partially correctly predicted by the multi-label classifier. We report an in-depth quantitative and qualitative analysis of these messages in the paper. The automatic categorisation results suggest that the multi-label classifiers have the potential to help educators and researchers identify research subjectivity and tolerate the multiplicity in cognitive presence categorisation. This study contributes to extending the literature on understanding cognitive presence in MOOC discussions.","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33465605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Making FAQ Chatbots More Inclusive: An Examination of Non-Native English Users’ Interactions with New Technology in Massive Open Online Courses 让常见问题聊天机器人更具包容性:大规模在线开放课程中非英语母语用户与新技术互动的研究

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-09-01 DOI: 10.1007/s40593-022-00311-4

Song-Ae Han, Min Liu, Zilong Pan, Ying Cai, Peixia Shao

引用次数: 3

Teaching How to Teach Promotes Learning by Teaching 教以教促学

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-31 DOI: 10.1007/s40593-022-00306-1

Noboru Matsuda, Dan Lv, Guoguo Zheng

引用次数: 0

Supporting College Choice Among International Students through Collaborative Filtering. 通过协同过滤支持留学生选择大学。

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-19 DOI: 10.1007/s40593-022-00307-0

Caitlin Tenison, Guangming Ling, Laura McCulla

{"title":"Supporting College Choice Among International Students through Collaborative Filtering.","authors":"Caitlin Tenison, Guangming Ling, Laura McCulla","doi":"10.1007/s40593-022-00307-0","DOIUrl":"10.1007/s40593-022-00307-0","url":null,"abstract":"In this paper we use historic score-reporting records and test-taker metadata to inform data-driven recommendations that support international students in their choice of undergraduate institutions for study in the United States. We investigate the use of Structural Topic Modeling (STM) as a context-aware, probabilistic recommendation method that uses test-takers' selections and metadata to model the latent space of college preferences. We present the model results from two perspectives: 1) to understand the impact of TOEFL score and test year on test-takers' preferences and choices and 2) to recommend to the test-taker additional undergraduate institutions for application consideration. We find that TOEFL scores can explain variance in the probability that test-takers belong to certain preference-groups and, by accounting for this, our system adjusts recommendations based on student score. We also find that the inclusion of year, while not significantly altering recommendations, does enable us to capture minor changes in the relative popularity of similar institutions. The performance of this model demonstrates the utility of this approach for providing students with personalized college recommendations and offers a useful baseline approach that can be extended with additional data sources.","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9390112/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33444473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards a Tutoring System to Support Robotics Activities in Classrooms – Two Wizard-of-Oz Studies 建立一个支持教室机器人活动的辅导系统——两个绿野仙踪研究

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-19 DOI: 10.1007/s40593-022-00305-2

S. Schulz, B. McLaren, Niels Pinkwart

引用次数: 0

Evaluating the Construct Validity of an Automated Writing Evaluation System with a Randomization Algorithm 基于随机化算法的自动写作评价系统结构有效性评价

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-09 DOI: 10.1007/s40593-022-00301-6

Matthew C. Myers, Joshua Wilson

引用次数: 0

An AI toolkit to support teacher reflection 支持教师反思的人工智能工具包

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-09 DOI: 10.1007/s40593-022-00295-1

Tanner M. Phillips, Asmalina Saleh, Gamze Ozogul

引用次数: 0

First-Year Engineering Students’ Strategies for Taking Exams 工科一年级学生应试策略

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-02 DOI: 10.1007/s40593-022-00303-4

Jakub Kuzilek, Z. Zdráhal, Jonas Vaclavek, Viktor Fuglík, J. Skočilas, A. Wolff

引用次数: 1

Automated Essay Writing: An AIED Opinion 自动化论文写作：AIED观点

IF 4.9

International Journal of Artificial Intelligence in Education Pub Date : 2022-08-02 DOI: 10.1007/s40593-022-00300-7

M. Sharples

引用次数: 28