The Effect Of Hypermedia Instruction On Achievement And Attitudes Of Students With Different Learning Styles
Why this work is in the frame
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Bibliographic record
Abstract
Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 1330 The Effect of Hypermedia Instruction on Achievement and Attitudes of Students with Different Learning Styles Malgorzata S. Zywno, Judith K. Waalen Ryerson University Abstract The goal of this ongoing action research project has been to increase student learning and satisfaction using an innovative approach to instruction, evaluation and interaction with students. A process control course in electrical engineering was redesigned, introducing collaborative, active learning using real-life applications. The course utilizes interactive hypermedia presentations and software simulations in the classroom and takes advantage of the interactive learning environment supported by WebCT1 software. This includes asynchronous communications (email and bulletin board) and online access to hypermedia materials. The evidence gathered during our empirical study revealed positive effects of hypermedia on students’ achievement. Our research also indicated that specific learning preferences are better accommodated through hypermedia-assisted instruction than through conventional instruction. I. Introduction The course was redesigned in 1997 to introduce active, collaborative learning, and to increase the exposure to real-life control problems. Student-centered, experiential learning has been shown to have a measurable effect on students’ achievement2, 3. It also has a positive impact beyond quantitative measures of academic outcomes, such as changes in students’ thinking, intellectual development, and personal growth4. The course designers therefore placed emphasis not only on the provision of a solid theoretical foundation, but also on the extension of the theory to practice, and on teamwork and communication skills. Real-time experiments in servo-motor control, demonstrations (fuzzy logic and optimal control of a 3D helicopter simulator), realistic design, testing, and implementation using advanced computer simulations (MATLAB and Simulink5) became an integral part of the course in and outside of the classroom6, 7. Non-technical skills became a larger part of course assessment, as groups of students prepared comprehensive design project reports, with attention paid to improving verbal and written communication skills. Course instructors also encouraged electronic communications via email to increase flexibility of student-instructor exchanges. Since much of the theory of process control relies on understanding fairly complicated mathematical concepts that can be enhanced through visualization, we next turned our attention to technology-enabled instruction and on-line support for the course8. Through continuing infrastructure investments over the past five years, many lecture theatres at Ryerson University have been permanently equipped to handle high-end Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright 2001, American Society for Engineering Education
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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) | 0.000 | 0.000 |
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 it