NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
Peer reviewed Peer reviewed
Direct linkDirect link
Jones, Joshua – Mathematics Teacher: Learning and Teaching PK-12, 2021
Aside from being culturally relevant, artificial intelligence is also supporting companies in making business decisions. Consequently, "workforce needs have shifted rapidly," resulting in a demand for applicants who are skilled in "data, analytics, machine learning, and artificial intelligence" (Miller and Hughes 2017). This…
Descriptors: Man Machine Systems, Artificial Intelligence, Educational Technology, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Rezaei, Mohammadsadegh; Bobarshad, Hossein; Badie, Kambiz – Interactive Learning Environments, 2021
The development of information technology and social networks has created new opportunities to access lifelong learning in the form of informal learning. In an informal learning environment, learning takes place via Communities of Practice (CoP). The learning success factors in online CoPs are learners' similarity in learning interests and…
Descriptors: Prediction, Electronic Learning, Communities of Practice, Information Technology
Streeter, Matthew – International Educational Data Mining Society, 2015
We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…
Descriptors: Probability, Error Patterns, Learning Processes, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Stoessel, Katharina; Ihme, Toni A.; Barbarino, Maria-Luisa; Fisseler, Björn; Stürmer, Stefan – Research in Higher Education, 2015
Current higher education is characterized by a proliferation of distance education programs and by an increasing inclusion of nontraditional students. In this study we investigated whether and to what extent nontraditional students are particularly at risk for attrition (vs. graduating) from distance education programs. We conducted a secondary…
Descriptors: Foreign Countries, Higher Education, Distance Education, Nontraditional Students
Peer reviewed Peer reviewed
Direct linkDirect link
Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili – Computers & Education, 2009
In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…
Descriptors: Dropouts, Prediction, Teaching Methods, Distance Education
Peer reviewed Peer reviewed
Direct linkDirect link
Huang, Yueh-Min; Huang, Tien-Chi; Wang, Kun-Te; Hwang, Wu-Yuin – Educational Technology & Society, 2009
The ability to apply existing knowledge in new situations and settings is clearly a vital skill that all students need to develop. Nowhere is this truer than in the rapidly developing world of Web-based learning, which is characterized by non-sequential courses and the absence of an effective cross-subject guidance system. As a result, questions…
Descriptors: Markov Processes, Transfer of Training, Probability, Internet
Shuford, Emir H., Jr.; Massengill, H. Edward – 1966
In decision-theoretic psychometrics, to determine the worth of individualizing instruction, equations are developed for expressing the cost and gain for applying an instructional sequence. This report is divided into three parts: first, a logical analysis of guessing; second, the effect of guessing on the quality of personnel and counselling…
Descriptors: Behavior, Branching, Computer Assisted Instruction, Cost Effectiveness
Peer reviewed Peer reviewed
Plummer, Robert; And Others – Mathematics Teacher, 1993
Uses a graphing calculator to predict the record for running a mile, throwing a shot put, and high jumping for any year in the future and the probable record for any year before statistics were kept, based on the statistical analysis of prior records. Data tables and a computer program are provided. (MDH)
Descriptors: Athletics, Data Analysis, Educational Technology, Graphing Calculators
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers