NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20250
Since 20240
Since 2021 (last 5 years)0
Since 2016 (last 10 years)2
Since 2006 (last 20 years)5
Audience
Laws, Policies, & Programs
Assessments and Surveys
Program for International…1
What Works Clearinghouse Rating
Showing all 7 results Save | Export
Geigle, Chase – ProQuest LLC, 2018
There are two primary challenges for instructors in offering a high-quality course at large scale. The first is scaling educational experiences to such a large audience. The second major challenge encountered is that of enabling adaptivity of the educational experience. This thesis addresses both major challenges in the way of high-quality…
Descriptors: Barriers, Educational Quality, Computer Assisted Testing, Educational Experience
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Peer reviewed Peer reviewed
Direct linkDirect link
Tzouveli, Paraskevi; Mylonas, Phivos; Kollias, Stefanos – Computers & Education, 2008
Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…
Descriptors: Educational Needs, Distance Education, Knowledge Level, Questionnaires
Park, Ok-choon; Tennyson, Robert D. – Contemporary Education Review, 1983
The theoretical rationales and procedures of five adaptive computer-based instruction models were reviewed: the mathematical model, the regression model, the Bayesian probabilistic model, the testing and branching model, and artificially intelligent instructional systems. Each model is assessed for contrast of methods and forms, identifiable…
Descriptors: Artificial Intelligence, Bayesian Statistics, Branching, Computer Assisted Instruction
Peer reviewed Peer reviewed
Fuchs, Lynn S.; And Others – Exceptional Children, 1994
An inductive assessment model for developing individualized instructional programs for special needs students is reviewed, followed by a discussion of how computer programs can help teachers solve logistical and technical problems of inductive assessment models and how expert systems can provide instructional advice. Expert systems for…
Descriptors: Computer Assisted Testing, Curriculum Based Assessment, Diagnostic Teaching, Elementary Secondary Education
Peer reviewed Peer reviewed
Direct linkDirect link
Gogoulou, Agoritsa; Gouli, Evangelia; Grigoriadou, Maria; Samarakou, Maria; Chinou, Dionisia – Educational Technology & Society, 2007
In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve learning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners' knowledge level, (ii)…
Descriptors: Teacher Education Programs, College Students, Student Attitudes, Foreign Countries
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection