ERIC ED466195: Developing a Typology of Students in a Web-Based Instruction Course.
Bibliographic record
Abstract
This paper argues that individual differences among undergraduate students are important factors to the effectiveness of asynchronous learning and that students' needs and perceptions must be taken into account in the design of Web-based instruction (WBI). A student typology is presented based on evidence from an ethnographic study of a WBI undergraduate course in the Education program at the University of Alberta. "EDPY202: Technology Tools for Teaching and Learning" is philosophically based on the perspective that learning is a process of constructing knowledge rather than a process of recording knowledge. Although EDPY202 is primarily a software tools literacy course, it does provide the students with some exposure to curriculum integration. Qualitative data were collected from an EDPY202 class with an enrollment of 700 students between September 1998 and June 1999. A total of 116 students volunteered to be interviewed. The great majority of the students, 72, were 19 to 24 years old; 28 students were 25 to 35 years old and 16 were over 35. The method used to investigate the course relied in part on participant observation and in-depth interviews in order to construct the categories through which the participants themselves interpreted their experience. The majority of students interviewed liked the course and spoke positively about the self-directed, active learning experience. Results are discussed in terms of: developing a new vocabulary; written versus spoken communication; difficulty with active learning; feelings of isolation and exclusion; overcoming technical problems; and marking criteria. (Contains 13 references.) (AEF)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.067 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".