Bibliographic record
Abstract
Abstract This article supports the view that online discussions should only be used for educational purposes. In the first half of the article, a heuristic for determining the educational viability of online discussions is offered. In the second half of this article, a model for determining viability is suggested. This model integrates the evaluation of online discussion into the discussion itself. In doing so, students are participating in determining whether or not the discussion been educationally viable. ********** Online discussion is often viewed as an educational novelty. Instructors sometimes require students to participate in online discussion simply to maintain students' interest and to increase their enjoyment of a course. While it is virtuous to keep students interested and make courses enjoyable, greater virtue can be found in educating students, which should stretch students' interests and expand the range of educational experiences that they enjoy. Online discussion should be more than novel; it should be educationally viable. To downplay educational viability is to ethically breach the implied contract that institutions of higher education have with society (Speck, 2000). The purpose of this paper is to offer a model for evaluating the educational viability of online discussion. I begin by offering a heuristic for determining educational viability. Then, I delineate a student-centered procedure for applying the heuristic to an online discussion. A Heuristic for Determining Educational Viability What is educational viability? For some, a viable education should teach people to think, to use their rational powers, to become better problems solvers (Gagne, 1980, p. 85); for others, educational viability has as much to do with the teachable heart as the teachable mind (McLaren, 1999, p. 50). Narrowing to educational viability in online adds some focus. Hacker & Neiderhauser (2000), for example, discuss the educational viability of online in terms of deep and durable learning (p. 53). Specifically, they argue that active collaboration among students, the effective use of examples, and appropriate feedback will motivate students toward educational success. Knowlton (2001) approaches the educational viability of online discussion through a connection to Bloom's cognitive taxonomy. (See Bloom, Englehart, Furst, Hill, & Krathwohl, 1956, for a full discussion of this taxonomy.) In short, for online discussion to be viable, students must go beyond summarizing and paraphrasing; they must also apply, analyze, synthesize, and evaluate. The variability in defining educational viability is important to academic freedom. Ultimately, instructors using online discussion must determine and defend their own educational rationales. Here, though, I suggest three heuristic questions for determining educational viability: Does the online discussion advance knowledge construction? Does the online discussion inspire personal narrative? Is online discussion a foundation for larger course assignments? Does the Online Discussion Advance Knowledge Construction? Philosophically, the notion of constructing knowledge is based on the view that knowledge and truth do not exist-or, at least, are not relevant-beyond a person's perception of that knowledge and truth (Duffy & Jonassen, 1991). Even if an objective reality exists, students can only subjectively know that reality. Therefore, knowledge is not something that students can receive from professors (Jonassen, 1991); students must create a personal view of the world (Jonassen, Davidson, Collins, Campbell, & Haag, 1995, p. 11). In an educationally-viable online discussion, students seek opportunities to learn (Canada, 2000) and share their opinions and perspectives about those opportunities. Because of the pluralism inherent to students' perspectives (Speck, 1998), conflicting viewpoints will emerge, and students will experience cognitive dissonance. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".