Records: 322
Open Educational Resources and Student Course Outcomes: A Multilevel Analysis
Jessie Winitzky-Stephens Jason Pickavance |
APA Citation
Winitzky-Stephens, J. R., & Pickavance, J. (2017). Open educational resources and student course outcomes: A multilevel analysis. The International Review of Research in Open and Distributed Learning, 18(4), 35-49. doi:10.19173/irrodl.v18i4.3118
Annotation
“Study conducted at a 2-year, public community college in Utah, the states largest open enrollment college, that opened many of their gateway and general education courses due to serving a majority low income students 37 courses utilized OERs over a four year span. Analyzed using multilevel modeling: student, instructor, and course levels. Controlled for student age, gender and race and level of course, developmental ed, 1000 level, and 2000 level. OER and non-OER courses were statistically . . . indistinguishable in independent samples t-tests (average course grade) and z-tests for proportions (pass and withdraw rates). Average grades in OER courses were significantly higher than their counterparts. Controlling for instructor-, course-, and student-level variables showed individual differences had a more significant impact on student grades and pass or withdrawal rate than instructors use of OER. Conclusion: There were no distinguishable difference in student grades or pass/withdraw rates between courses using OER and courses using traditional materials.
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Picturing Them Right in Front of Me: Guidelines for Implementing Video Communication in Online and Blended Learning
Richard West Jason Jay Matt Armstrong Jered Borup |
APA Citation
West, R. E., Jay, J., Armstrong, M., & Borup, J. (2017). “Picturing them right in front of meâ€: Guidelines for implementing video communication in online and blended learning. TechTrends, 61(5), 461-469. doi:10.1007/s11528-017-0208-y
Annotation
” Published findings from a larger study interviewing students and instructors about their use of asynchronous video in blended courses. Feedback videos are best when students consider them prompt meaning sent with ample time to use the feedback meaningfully or to prepare for future assignments. To make feedback videos more effective, write out your ideas first, provide bulleted summary notes to students, avoid re-recording in a quest for ‘perfection’, Keep videos under 10 minutes but . . . ideally as short as possible while still conveying your message, consider a general group feedback video for comments that would be beneficial to the whole class, and understand your technological limitations (i.e. lack of bandwith, too large of files). To improve personability, embrace imperfection through the use of humor, emotions, or even informal language, be authentic share things about yourself, be conversational, let your personality and personal interests come through.To improve effectiveness, use a variety of methods-don’t solely rely on video communication for everything, it is good practice when more personal support is needed, but can have a negative impact when an instructor is frustrated or has negative emotions regarding a project. Text may be more effective when giving feedback that is minor, specific, and straightforward. Screencast videos allow the instructor to contextualize comments to a specific portion of a project, recording the video so it is a screencast while still displaying the instructor talking (talking head in the corner style) this allows students to best utilize feedback while still seeing the instructor as human.Consider your audience when asking students to create and receive video messages, some students may feel more comfortable communicating and receiving feedback via video, while others may prefer text.The best time for video is at the beginning of the semester to help establish presence. Inviting students to create intro videos can add to text based communication in the future since students can then better understand each other’s ‘voice.’ Conclusion: Video is a strong tool for giving feedback in a blended environment if done in a way that is prompt, clear & concise, and showcases the instructor’s humanity.
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Using course-level factors as predictors of online course outcomes: a multi-level analysis at a US urban community college
Claire Wladis Katherine Conway Alyse Hachey |
APA Citation
Wladis, C., Conway, K., & Hachey, A. C. (2017). Using course-level factors as predictors of online course outcomes: A multi-level analysis at a US urban community college. Studies in Higher Education, 42(1), 184-200. doi:10.1080/03075079.2015.1045478
Annotation
“Study conducted at a 2-year, large, public urban community college in the Northeast designated as an MSI. This study assesses the extent to which course level factors predict online course outcomes. Analyzed a data set of 2,330 online and face to face students over a span of 6 years, chosen by selecting courses where an instructor taught online and face to face in the same semester, choosing 3 online and 3 face-to-face sections. Completed a multi-level logistic regression with successful online . . . course completion (C or better) as the dependent variable. There was a significant difference in successful course completion rates for online courses taken as electives compared to major requirements, with electives having a lower rate of succes. Lower level courses had a highly significant lower successful course completion rate than upper level courses but the success rates were statistically significantly higher in online courses than in face-to-face counterparts. Conclusion: Students have a lower success rate with online courses that are electives when compared to major requirements and a lower success rate with online lower level (100 level) courses compared to higher level online courses but succeed at a higher rate than students in those same face-to-face courses. Students are most successful in higher level, major requirement courses. Study calls for institutions to focus their interventions on lower level online courses to bring their success rates in line with f2f lower level foundational courses.
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Using Design-Based Research in Higher Education Innovation
Cristi Ford Darragh McNally Kate Ford |
APA Citation
“Ford, C., McNally, D. & Ford, K. (2017). Using design-based research in higher education
innovation. Online Learning, 21(3), 50-67. doi: 10.24059/olj.v%vi%i.1232″
Annotation
“Using a design-based research methodology, the study sought to understand how and why a specific intervention works in practice. Faculty, staff, and practioners comprised the research team that used andragogy, an adult learning theory, as a framework to understand the impact of a particular adaptive courseware, Realizeit, on student learning in “Obstacle Courses,†courses that have high enrollment but low success rates.
In the final version of the pilot study, the research team utilized . . . Randomized Control Trial to determine the impact of Realizeit on student learning. Within Accounting courses, data was “gathered on student interaction with the platform, student quiz and exam grades, student discussion posts (qualitative and quantitative), and student impressions and experience with the platform†(p. 56). These measurements were consistent for the treatment and control groups. The study also relied on interviews with instructors of the courses and students enrolled in the courses. There were minimal differences found between the treatment and control group regarding challenges with the courses, perceptions of instructors, or course material.
The research findings are similar across the different iterations of the pilot study. The quantitative results indicate that students enrolled in a course section that utilized RealizeIt are more likely to finish the course successfully than those who were not in the course. Additionally, students enrolled in a course section utilizing the adaptive courseware were more likely to earn a higher grade than their counterparts.
Readers who are interested in design-based research (DBR) will find this article helpful in its explanations of the advantages and implications of the methodological approach used in the study. The authors take time to explain how to conduct a study that is based in DBR, multimethods, and different iterations of a pilot study.
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What Impacts do OER Have on Students? Students Share Their Experiences with a Health Psychology OER at New York City College of Technology
Cailean Cooney |
APA Citation
Cooney, C. (2017). What impacts do OER have on students? Students share their experiences with a health psychology OER at New York City College of Technology. The International Review of Research in Open and Distributed Learning, 18(4), 155-178. doi:10.19173/irrodl.v18i4.3111
Annotation
“This study evaluated the impact of OER’s on student’s academic experiences at a MSI. his study was conducted at New York City College of Technology (City Tech), of the City University of New York (CUNY), a comprehensive, 4-year, public, non graduate degree granting, MSI college located in Brooklyn. Learning materials were curated and posted or linked out to on a course website open to the students and the public. This study gathered data from 67 end of course student surveys and 6 45-minute . . . interviews. Students most often accessed course materials on a personal laptop, followed by a smart phone and then college computer. Biggest challenge was accessing wifi on campus (27%), otherwise students found it easy to navigate to course materials. Students expressed that the convenience of accessing the course and it’s materials anywhere allowed them to better engage with the content, participate in the course, and complete their assignments. Conclusion: Students reported OER use in the course lead to them developing improved learning habits and positively influenced their motivation to learn.
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Adaptive Learning in Psychology: Wayfinding in the Digital Age
Charles Dziuban Patsy Moskal Jeffrey Cassisi Alexis Fawcett |
APA Citation
“Dziuban, C. D., Moskal, P. D., Cassisi, J., & Fawcett, A. (2016). Adaptive Learning in Psychology: Wayfinding in the Digital Age. Online Learning, 20(3), 74-96.
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Annotation
“In this pilot study, the authors work in partnership with an adaptive learning technology vendor to evaluate students’ affective, behavioral, and cognitive reactions to the platform. Through a questionnaire, 292 undergraduate students enrolled in an online Psychology class at a large, metropolitan university were asked about their perceptions of learning through the adaptive learning platform RealizeIt. According to the authors, the platform is based on “probablistic reasoning using . . . Bayesian estimation procedures,†which “utilizes students’ initial baseline results to estimate their position in a curriculum framework”” (p. 77). Progressing through the course, Realizeit suggests alternative paths for learning. As a result, “continuous updates of students’ ability estimates, the knowledge they have acquired, those objectives that still require mastery and recommendations for optimal paths through the course material”” (p. 77).
Utilizing quantitative and qualitative questions, the questionnaire measured student perceptions of learning via Realizeit. The researchers also studied the ways in which the students engaged with the learning material, the instructor, and their peers as they progressed through the course in a self-paced manner. Finally, the researchers compared students who successfully completed each module to those who were unsuccessful.
The outcome measures for the study are knowledge state and percentage of nodes covered. The authors of the study explain, “The reliability was computed using coefficient alpha (Cronbach, 1951). Frequencies for each of the survey items were calculated and examined along with means and standard deviations for those who engaged with various features of Realizeit”” (p. 82).
The findings suggest that the majority of students expressed satisfaction about their learning experience via the Realizeit platform and believed that the platform effectively evaluated their knowledge in the subject. Additionally, most students indicated that the platform was easy to use. In regard to behavior, over half of the study participants “always or quite often followed the system recommendation†and the majority shared that they did not have technical issues while using the system. Finally, students indicated that they felt as if they interacted less with their peers when using Realizeit than when not using the platform. Yet, the majority of students indicated that they did not need or want increased interaction.
Based on these findings, the authors of the study argue that, like any online class, course design is of particular importance. This is especially true for adaptive learning platforms that are based on faculty control in the designing process. The authors recommend that students be provided adequate time for learning and that instructors recognizing the importance of students’ prior knowledge of the subject before engaging with the platform.
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An Examination of Student Outcomes and Student Satisfaction in a Flipped Learning Environment: A quasi-experimental design
Angela Lee |
Annotation
For this study, a two-by-two quasi-experimental design was established to examine the results by Learning Environment and Gender (grouping variables) on selected Dependent Variables. The purpose of this study was to explore the mean differences between Learning Environment and Gender based on the Dependent Variables, which was conducted in introductory sociology courses.111 participants, 58 female 44 male. Majority freshman and sophomores. Student outcome measures occurred in three different . . . ways: pretest and posttest
assessment, three lower-order learning quizzes, and a higher-ordered unit exam. Using a two-way MANOVA, the research question was answered. The research question was divided into three subquestions and analyzed through multivariate statistics. First, the interaction effects of Learning Environment by Gender on the Dependent Variables were reviewed from Pillai’s Trace. The results indicated that there were no
significant interaction effects. Then, the main effects for Gender on the Dependent
Variables was computed. No significant main effects were found. Finally, the effect of
Learning Environment was analyzed. The results revealed that differences did exist by
Learning Environment. Based upon the MANOVA findings, seven one-way ANOVA
tests were conducted. The subsequent post hoc tests exposed that there was a group
difference with Learning Environment as the grouping variable on the Dependent
Variables, Race/Ethnicity Quiz and the Higher-Ordered Unit Exam. Using a two-way MANOVA, the research question was answered. The research question was divided into three subquestions and analyzed through multivariate statistics.
First, the interaction effects of Learning Environment by Gender on the Dependent
Variables were reviewed from Pillai’s Trace. The results indicated that there were no
significant interaction effects. Then, the main effects for Gender on the Dependent
Variables was computed. No significant main effects were found. Finally, the effect of
Learning Environment was analyzed. The results revealed that differences did exist by
Learning Environment. Based upon the MANOVA findings, seven one-way ANOVA
tests were conducted. The subsequent post hoc tests exposed that there was a group
difference with Learning Environment as the grouping variable on the Dependent
Variables, Race/Ethnicity Quiz and the Higher-Ordered Unit Exam.
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Ed Undersecretary Shares Obama Administration’s Home Stretch Vision
J. Carter |
APA Citation
Carter, J. (2016, July 11). Ed undersecretary shares Obama administration’s home stretch vision. Education Drive. Retrieved from: http://www.educationdive.com/news/ed-undersecretary-shares-obama-administrations-home-stretch-vision/422314/
Annotation
This 2016 news article looks at the Obama administrations educational plans for their final 200 days. Department of Education’s Undersecretary Ted Mitchell convened a conference to encourage policy makers, administrators, and educators to think about the new educational environment and demographic changes that higher education will increasingly see.
About half (13 million) college students attend community college. Several national education foundations, community college presidents, and . . . educational policy advocates say they hope to see changes in higher education that meet the current and future students’ needs. These include a more fluid ability to enter and exit the job market while attending college and greater internet access.
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Mapping Research Trends from 35 Years of Publications in Distance Education
Olaf Zawacki-Richter Som Naidu |
APA Citation
Zawacki-Richter, O., & Naidu, S. (2016). Mapping research trends from 35 years of publications in Distance Education. Distance Education, 37(3), 245-269.
Annotation
Using a text-mining tool Leximancer, this article reports the research trends in Distance Education journal between 1980 and 2014. Titles and abstracts of 515 peer-reviewed articles are analyzed and core concepts (listed below) is extracted. Result of text mining indicates alternating waves of institutional (meso-level) and individual (micro-level) research focus.
Phase 1 Institutional focus: Professionalization and institutional consolidation (1980-1984), instructional design and educational . . . technology (1985-1989)
Phase 2 Individual focus: Quality assurance in distance education (1990-1994) Student support and early stages of online learning (1995-1999)
Phase 3 Institutional focus: The emergence of the virtual university (2000-2004) Collaborative learning and online interaction patterns (2005-2009) Interactive learning, MOOCs and OERs (2010-2014)
Capturing trends on topics and methods is essential for the advancement of research on distance education.
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Models of Administration for Online Learning Programs in the U.S. Higher Education Institutions
Phu Vu Richard Meyer Jude Cepero |
APA Citation
Vu, P., Meyer, R., & Cepero, J. (2016). Models of administration for online learning programs in the U.S. higher education institutions. Journal of Applied Educational and Policy Research, 2(1), 24-31.
Annotation
“This mixed-method research study consisted of an online survey, which sought to answer the following questions: (1) “What is the most common model of online learning program administration in U.S. higher education?â€; (2) “What do people, including staff and administrators who are involved in the online learning programs, think about their own institution’s program administration model?â€; and (3) “Which model of online learning program administration tends to be more effective?†. . . (p. 26). The sample for the research consisted of 85 higher education staff and administrators who worked with online learning in the United States recruited from the “Institute for Emerging Leadership in Online Learning†(IELOL) alumni list. The data were analyzed quantitatively and qualitatively, using frequencies and basic statistics for close-ended responses and “word counts” and thematic analysis for open-ended responses. The institutional model that the researchers labeled “Centralized Administration,†consisting of a centralized campus online learning unit reporting to the office of a Vice Chancellor or Chancellor/President, appeared as the most common online learning administration model. Approximately 61% of survey respondents worked in a variety of institutions that represented the “Centralized Administration†model.The other roughly 39% of respondents, all representing large universities, appeared to work with a “Decentralized Administration†model, where online learning units are fragmented across campus within individual colleges and directly report to College Deans. Respondents representing the “Centralized Administration†model “graded†their programs higher, compared them more favorably to other online programs, and were more satisfied with their programs than the respondents from “Decentralized Administration†models. The researchers also identified four themes across respondents’ open responses that appeared relevant regardless of the institutional model. The researchers labeled these themes as: (1) “faculty’s competence and acceptanceâ€; (2) “high-level administration supportâ€; (3) “staffing issuesâ€; and (4) “quality assurance†(p. 28). The researchers note that the “Centralized Administration†model may appear more effective due to a consistent, cross-campus approach but “high-level administration support†appeared important to respondents from both models, as units fragmented across campus still ultimately report to higher-level administrators.
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