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Accessible Elements: Teaching Science Online and at a Distance

2010· book· en· W2514389814 on OpenAlexaff
Erna Dominey, Peter Enman, Kathy Killoh, Natalie Olsen, Michael Moore, Terry Anderson

Bibliographic record

VenueAthabasca University Press eBooks · 2010
Typebook
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsAthabasca University
Fundersnot available
KeywordsDistance educationComputer scienceOnline teachingMathematics educationWorld Wide WebData sciencePsychology

Abstract

fetched live from OpenAlex

The American Journal of Distance Education X • accessible elements around the country on railway trains.Looking for a simpler and less costly solution, my assignment was related to his work on the concept of the home experiment kit.This would be a package of materials and equipment that could be loaned to the student, who would use it in conducting science experiments at home.It was one of many ideas that Wedemeyer had been discussing with friends in the United Kingdom who were in the process of setting up the Open University, where it became extremely successful as sophisticated and ingenious home experiment kits were developed on an industrial scale (see Chapter 10).Forty years after those early initiatives -and in spite of the example of the Open University, which has not only shown that science can be taught at a distance, but has become a world center of high quality science -the prejudice that science can only be taught faceto-face is still widespread, especially in the United States.Indeed, innovative course and program proposals frequently fail to get off the ground because of very ill-informed assertions by classroom teachers that distance teaching of science is not possible.It should be a matter of some surprise -now that we have Dietmar Kennepohl and Lawton Shaw's book before us -to realize how long it has taken for someone to produce a book to challenge this prejudice, indeed to begin to describe the problem and to document some of the ways in which it has been tackled.Further evidence of the slowness of the educational community to deal with the challenge -and opportunity -of distance teaching in the sciences is provided by the number of articles that have appeared in the quality research journals.In more than twenty years, the American Journal of Distance Education has received only one publishable research-based article having "science" in its title; this was an article on the subject of science teaching in high schools (Martin & Rainey, 1993).Added to this, there have been descriptive, i.e., non-research based reports, in the Journal's "Grassroots" section describing isolated experiences in science teacher education (Jaeger, 1995), and another about an attempt Foreword • XIII as lending themselves to a constructivist pedagogy.The big question, of providing laboratory experiences, is the subject of a full section, in my opinion one of the core questions in this book, and then a final section deals with some issues of the logistics and infrastructure of program delivery.This book will, I hope, be read by everyone with an interest in education.This is not only for science educators or distance educators alone.Certainly one hopes that teachers of science in the classroom -most of whom are likely to be called on in the future to teach at a distance at least in blended learning conditions -as well as those who already do teach at a distance, and also the administrators and policy makers who have to allocate and manage the resources that are available for science education will study this book carefully and glean from it some of the valuable ideas it provides for the expansion and improvement of distance education in the sciences.Surely our students deserve better programs, the out-of-school population needs more opportunity of continuing education in the sciences, and society deserves and needs a better return on its education and training investment in the sciences than it has enjoyed until now.If this book goes even a short way toward sensitizing these populations to the challenges of teaching science at a distance and also the enormous potential for society and the individual of upgrading our response to that challenge, it will indeed prove to be a most important work -besides being a thoroughly enjoyable read. ReferencesAbdel-Salam, T.M., Kauffmann, P.J., & Crossman, G.R. (2007).Are distance laboratories effective tools for technology education?The American Journal of Distance Education, 21(2), 77-92.Jaeger, M. (1995).Science teacher education at a distance.The American Journal of Distance Education, 9(2), 61-75.Martin, E.D., & Rainey, L. (1993).Student achievement and attitude in a satellite-delivered high school science course.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.056
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0560.010

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.

Opus teacher head0.020
GPT teacher head0.288
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations40
Published2010
Admission routes1
Has abstractyes

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