Three Institutions, Three Approaches, One Goal: Addressing Quality Assurance in Online Learning

Britto, Marwin; Ford, Cristi; Wise, Jean-Marc

doi:10.24059/olj.v17i4.402

Cited by 22 publications

(14 citation statements)

References 16 publications

(19 reference statements)

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“…The final step involved conducting thematic analyses of the students' open-ended comments; extracting related concepts and determine the dominate themes in the two learning environments. Britto et al (2014) attempted to establish benchmarks for the online educational experience from three universities, we employ a similar technique but, in an attempt, to understand the SAI from two instructors teaching the same course and using the same materials and guidelines. We did not seek to understand individual teaching differences; rather, our aim was to better understand how students perceive instruction as communicated through their completion of the open-ended section of the SAI in the two learning environments.…”

Section: Methods Proceduresmentioning

confidence: 99%

Untitled

2019

SPRT

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This study explored the relationship between the athletic identity and career maturity of women's basketball student-athletes. It specifically looked at the differences in athletic identity and career maturity based on the studentathlete's level of competition, race, year in school, socioeconomic status, and professional athletic career aspirations. A convenience sample of 209 women's basketball student-athletes from NCAA Divisions I, II, and III, as well as NAIA institutions participated in the study. Participants completed a demographic questionnaire along with the Career Maturity Inventory-Revised Attitude Scale and the Athletic Identity Measurement Scale. The findings suggest that within this sample of women's basketball student-athletes, stronger identification with the athletic role is associated with lower levels of career maturity. Results also indicated that NCAA Division I student-athletes had significantly higher levels of athletic identity and significantly lower levels of career maturity than Division II student-athletes. Likewise, women's basketball student-athletes that planned to pursue a professional basketball career (n = 76) displayed significantly higher levels of athletic identity and significantly lower levels of career maturity than those that did not (n = 133). As research suggests, less than 1% of women's basketball student-athletes will compete professionally (NCAA, 2017a). However, based on the findings of the current study, 36.4% (n = 76) of the women's basketball student-athletes sampled planned to pursue a professional basketball career upon graduating. The results of this study can assist individuals working with these student-athletes (e.g., coaches, counselors, professors) to intervene and ultimately assist women's basketball student-athletes with preparation for life after sports. Many statistics are used to measure the productivity of hitters in Major League Baseball, such as the number of home runs and the number of runs batted in a season. However, comparing the talent of individual players across time is difficult as rules and technologies change. In this paper, we propose applying a practice commonly utilized in the finance literature to compare the performance of individual stocks and other assets, namely, we "benchmark" the productivity of each player's performance to players in the same time period. Applying our benchmarking strategy to annual Major League Baseball data from 1871-2010, we find that Babe Ruth is the greatest hitter of all time.

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Section: Methods Proceduresmentioning

confidence: 99%

Untitled

2019

SPRT

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“…QA processes can be established at the macro or micro levels. Macro-level QA processes manage institutional oversight; a micro level QA process may manage student experiences, such as offering support in orientating students to an online learning environment through the types of engagement tools being offered in the course delivery method [52]. Achieving quality teaching and learning is an important and complex effort involving multiple interacting levels and dimensions; these include managing the technological educational infrastructure, designing curricula and courses, training educators, and preparing students [53].…”

Section: Quality Assurancementioning

confidence: 99%

“…A comparative study suggested that although a uniform approach is absent, there are quality standards that institutions can effectively implement to address QA in online learning [52]. A QA outline that is template-and checklist-driven was proposed that is dynamically and iteratively intertwined with the e-learning development process [57].…”

Section: Quality Assurancementioning

confidence: 99%

Quality Assurance Framework for the Design and Delivery of Virtual, Real-Time Courses

2021

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Designing and delivering outcome-based courses that emphasize learner-centric educational discourse and active learning is challenging, especially in online learning environments. Ensuring quality in the design and delivery of such courses in the virtual space requires a well-defined framework with key constituents that interact based on ordered sequences of events. Despite the pressing need for a quality assurance system for today’s virtual, real-time courses, such a system has not been systematically designed. A coherent quality assurance system requires a clear framework that defines the interacting constituents. This work proposes a conceptual and generic “Quality Assurance” (QA) framework, based on experiences primarily in Science, Technology, Engineering, and Mathematics (STEM) fields, for the effective design and delivery of outcome-based virtual, real-time courses that incorporate active learning practices. This Quality Assurance framework may be adjusted to serve as a blueprint that, once adjusted by institutions to accommodate their missions, guides institutions in developing or amending their policies and procedures for the design and delivery of virtual, real-time courses; in addition, such a framework is important for institutions to develop Quality Assurance systems that integrate mechanisms for continuous improvement. The proposed quality assurance framework includes three constituents: a “Teaching and Learning Support” (TLS) that trains educators on pedagogical approaches and the capabilities of the institution’s Learning Management System (LMS); an “Information and Communication Technology Support” (ICTS) that assists educators with the technologies and tools available in the learning management system; and a “Course Management System” (CMS) that encapsulates course design, delivery, and assessment; this study focuses primarily on this “Course Management System” constituent.

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“…To summarize, the ten rubrics reviewed in this study show similarities in the dimensions addressed and the rating scales used, but they differed in their focus for evaluation. These differences seem reasonable, as all higher education institutions have different needs, interests, and criteria for evaluating online courses (Britto, Ford, & Wise, 2013). However, from a research perspective, key questions remain: which dimensions are more important in evaluating the quality of an online course?…”

Section: Course Quality Rubricsmentioning

confidence: 99%

The Validity and Instructional Value of a Rubric for Evaluating Online Course Quality: An Empirical Study

Lee

Recker

Yuan

2020

OLJ

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This study investigates the validity and instructional value of a rubric developed to evaluate the quality of online courses offered at a midsized public university. This rubric is adapted from an online course quality rubric widely used in higher education, the Quality Matters rubric. We first examine the reliability and preliminary construct validity of the rubric using quality ratings for 202 online courses and eliminate 12 problematic items. We then examine the instructional value of the rubric by investigating causal relationships between: (a) course quality scores, (b) online interactions between students, instructors, and content, and (c) student course performance (course passing rates). A path analysis model, using data from 121 online courses enrolling 5,240 students, show that only rubric items related to learner engagement and interaction have a significant and positive effect on online interactions, while only student-content interaction significantly and positively influence course passing rates.Keywords: online course quality, rubric, online interactions, rubric reliability, rubric validity, quality matters rubric Lee, J.E., Recker, M., & Yuan, M. (2020). The validity and instructional value of a rubric for evaluating online course quality: And empirical study. Online Learning, 24(1), 245-263.The number of college students taking online courses has increased dramatically over the past decade, with almost 31% of U.S. undergraduate students (about 5.2 million) having taken at least one course online as of the 2016 fall semester (McFarland et al., 2018). With this rapid growth in the number of online courses, evaluating their quality has taken on a new urgency. While many approaches have been developed to evaluate online course quality for example, surveys, checklists, observations, peer reviews, and expert reviews-one common way is through quality rubrics

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Three Institutions, Three Approaches, One Goal: Addressing Quality Assurance in Online Learning

Cited by 22 publications

References 16 publications

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Quality Assurance Framework for the Design and Delivery of Virtual, Real-Time Courses

The Validity and Instructional Value of a Rubric for Evaluating Online Course Quality: An Empirical Study

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