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Record W7037702513

Exploring the Self-efficacy of Graduate Students in an Online Post-professional Health Management Program

2019· article· en· W7037702513 on OpenAlexaboutno aff

Bibliographic record

VenueScholarly Commons (University of the Pacific) · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsExperiential learningOnline learningOnline participationEducational technologyLearning ManagementTime managementPerceptionScale (ratio)Active learning (machine learning)
DOInot available

Abstract

fetched live from OpenAlex

Background: A student’s online learning self-efficacy is their perception of their abilities to complete tasks required of online learners. The 22-item online learning self-efficacy scale (OLSES) examines perceptions of self-efficacy in three domains: learning in the online environment (LEARN, 10 items), time management (TIME, 5 items), and technology use (TECH, 7 items). In the development of the OLSES, undergraduate students with online learning experience were found to report higher OLSES scores than those without online learning experience. Examining the online learning self-efficacy among adult learners in a graduate program can provide information to program leadership that could guide the development of new resources to promote student success. The purpose of this study was to examine: 1) perceptions of online learning self-efficacy among graduate students prior to their entry in an online post-professional health management program in Canada, 2) whether or not there was a relationship between the student’s previous online learning experience, age, program stream and reported comfort with online learning, and 3) whether OLSES scores changed following two semesters. Methods: The Master of Health Management Program is an online program offered to regulated health professionals. Through course work, including experiential learning opportunities, students gain the knowledge and skills to move into and excel in health management roles. An online survey with demographic questions, the OLSES, and a global rating of comfort with online learning (rated 1-7) was distributed to all students in the part-time (PT- 32 months) and full-time (FT- 12 months) program streams during the first two weeks of the first semester (Round 1). The same survey was distributed during the last two weeks of the second semester (Round 2). The Wilcoxon rank-sum test was used to examine differences in total and domain OLSES scores related to students’ previous online learning, age (≤30 years>), program stream and comfort with online learning in Round 1. After Round 2, paired sample t-tests were used to compare differences in OLSES from Rounds 1 to 2. Independent sample t-tests were conducted to evaluate whether OLSES scores were different depending on program stream or previous online learning experience. This study was deemed to be a quality improvement initiative and thus was exempt from ethics board review. Results: Forty-nine students (39 women, 10 men, mean age 38 years) completed Round 1 in September 2018 (79% response rate). Thirty-seven students were in the PT stream, 12 were in the FT stream. Eleven (22%) had no previous experience with online learning; students' mean comfort rating was 5. Unlike the results in with the undergraduate students, no statistically significant differences were found between the students’ previous online learning experience and the total OLSES or any domain scores (all p>0.5). Similarly, there were no differences in OLSES scores between age and program streams. There were statistically significant differences for the total OLSES score (p=0.04), LEARN scores (p=0.03) and TECH scores (p=0.01) when comparing students with higher and lower ratings of comfort with online learning. Twenty four students (19 women, 5 men, mean age 38 years) completed both rounds of the survey. The 17 students in the PT stream had completed 2 courses, while the 7 students in the FT stream had completed 6. There were statistically significant differences in the students’ total (p=0.0001), LEARN (p=0.0002), TIME (p=0.001) and TECH (p=0.000) scores between Rounds 1 and 2. There wereno statistically significant changes noted in the students’ reported comfort with online learning (p=0.66). Furthermore, there was no evidence of the impact of previous online learning nor program stream in the changes to the OLSES scores. Conclusion: In contrast to undergraduate learners, students’ previous online learning experience did not appear to influence the graduate students’ OLSES scores. This may be related to the range of online learning activities that adults currently engage in. There was a statistically significant change in all students’ OLSES scores (total, and 3 domains) after two semesters in this post-professional health management graduate program regardless of the number of courses taken. Future research could examine whether a significant change in the students’ online learning self-efficacy would occur following one course. The results of this study suggests the importance of making additional resources available to the students to help them increase their comfort with online learning in all three domains of the OLSES, and especially with technical aspects of the online learning process. Based on the results, new modules will be developed and made available to students prior to the start of the program in an effort to increase their comfort in online learning.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.104
GPT teacher head0.267
Teacher spread0.163 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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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Citations0
Published2019
Admission routes1
Has abstractyes

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