A meta-analysis of course evaluation data and its use in the tenure decision

1984 ◽  
Vol 21 (2) ◽  
pp. 150-158 ◽  
Author(s):  
L. W. McCallum
1987 ◽  
Vol 14 (1) ◽  
pp. 51-53
Author(s):  
David S. Glenwick

A graduate course in mental health administration that combines classroom, field visit, and practicum components is described. The course provides students with an overview of the major responsibilities, concerns, and issues in the management of mental health facilities. Course evaluation data indicate that the course has been meeting its goal of stimulating students' interest in this area of increasing involvement by psychologists.


2015 ◽  
Vol 18 (2) ◽  
pp. 62-75 ◽  
Author(s):  
Rik Lemoncello

Blended learning, also known as hybrid courses or flipped classrooms, combines face-to-face and online learning to alter the sequence of knowledge acquisition; students engage in content learning before class in order to maximize in-class time for active learning. Active learning in class helps produce significant learning as learners practice with, engage with, and apply pre-class learning. In this manuscript, the author describes the development of a required undergraduate course, Anatomy and Physiology for Speech and Swallowing, from a traditional format to the hybrid blended learning format, as well as program evaluation data. When compared to the traditional format with active learning, the hybrid format with active learning produced similar outcomes in terms of final grade distribution. Analysis of data from teaching the A&P course as a hybrid for 3 years revealed a significant correlation between time spent on-task online with pre-class learning tutorials and final grades. The author also provides qualitative analysis of course evaluation data and lessons learned, and includes detailed information to help readers design effective hybrid courses.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S886-S886
Author(s):  
Edmund H Duthie ◽  
Kathryn Denson ◽  
Deborah Simpson ◽  
Steven Denson ◽  
Amanda Szymkowski

Abstract Perceptions of an educational experience’s value impact learning. “Hands-on” activities promote deeper learning and retention. Educators may jettison more poorly rated sessions, not having time for perceived content revisions based on evaluation data. We sought to determine if simply changing the sequence of a session’s activities, using the same content, improved learner evaluations. Using a session focused on application of resources for dementia patient caregivers, we provided two versions of the same content to 2 groups of clinicians. In session version #1 (V1), participants were asked about caregiver stresses and barriers and then viewed two video triggers of a dementia patient and a stressed family caregiver. Participants then identified the caregiver’s struggles and recommended resources. At the session’s end they were provided with a Geriatric Fast Fact (GFF) (www.geriatricfastfacts.com) that hyperlinked to a variety of evidence-based resources by topic. In session version #2 (V2), only the content was flipped. The GFF was presented prior to the video, with clinicians were then tasked to identify best resources using the GFF. The V2 cohort rated the session higher than V1 cohort on a 4-point scale (1= Excellent, 4= Poor). Overall quality of learning plan (V1 =1.4 ; V2 =1.3); Would you recommend the session to peers (V1 = 1.5; and V2 =1.2) and Overall course evaluation (V1 = 1.5; V2. = 1.4) all improved. Using learner evaluations to revise the sequence of the same content was an effective educational strategy. Don’t throw the baby out with the bathwater!


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Ziqiao Wang ◽  
Ningning Yu

During the recent epidemic period of COVID-19, online courses have become an important learning form for college students. However, online learning cannot communicate face to face in class and position students’ abilities accurately, and there are many problems and limitations such as one-way evaluation, for example, neglecting of process evaluation and simple evaluation form. Therefore, how to construct the evaluation system of online course teaching and make effective use of the evaluation mechanism becomes an urgent problem. Based on the big data mining of online course evaluation data, the online course evaluation optimization architecture based on process evaluation is proposed. The optimization of online course evaluation is analyzed from online course evaluation data and student comments using deep learning and collaborative filtering technology. This includes improving teacher teaching and improving student learning efficiency. Data experiment proves that the proposed algorithm can provide an optimal evaluation strategy, guarantee the students’ learning quality, and improve the efficiency of online course.


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