Predictors of Success in Large Enrollment Introductory Courses: An Examination of the Impact of Learning Communities and Virtual Learning Resources on Student Success in an Introductory Level Sociology Course

Dietz, Tracy L.

doi:10.2307/3211522

Cited by 29 publications

(34 citation statements)

References 5 publications

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“…According to Wang and Newlin (2000), the activities students engaged in during online learning can affect their final scores, with students who participate in academic activities at high levels performing better than those who do not. The number of times students logged into the LMS is believed to be a strong predictor of student academic performance in online learning (Dickson, 2005;Dietz, 2002). In the present study, the number of times students logged into the LMS and how long they stayed on the LMS were recorded in the LMS log file as students' utilisation of the LMS for the whole semester while they were taking the courses.…”

Section: Participation In Online Academic Activitiesmentioning

confidence: 91%

“…For example, given the positive effect of teacher comments on student achievement in many studies (Cavanaugh et al, 2005;Dickson, 2005;Ferdig et al, 2005;Peters, 1999), the negative effect of this factor in Algebra II (first half) group found in this study emphasises the need for more examination of the form and content of teacher comments or feedback for more insightful explanation. It is also surprising to the authors that the number of times students logged into the LMS was found to be negative and significant on student final score in Algebra II (both first half and second half) groups, because other studies (for example, Dickson, 2005;Dietz, 2002) have found that this factor can positively predict student success in online learning. Future study can be conducted on the activities in which students are engaging each time they log into the LMS for finer explanation of these findings.…”

Section: Conclusion and Future Studymentioning

confidence: 94%

“…Surprisingly, the effect of the number of times students logged into the LMS on student final score was negative and significant for Algebra II (both first half and second half). This contradicts the belief that the number of times students logged into the LMS is a strong and positive predictor of success in online learning (Dickson, 2005;Dietz, 2002). It is possible that if students were logging into the course environment more often, they were staying and working for shorter time periods, negatively impacting their concentration on their studies.…”

Section: Open Learning 157mentioning

confidence: 96%

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Factors influencing student academic performance in online high school algebra

Liu

Cavanaugh

2012

Open Learning: The Journal of Open, Distance and e-Learning

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This paper describes the effect of teacher comments, students' demographic information and learning management system utilisation on student final scores in algebra courses in a K-12 virtual learning environment. Students taking algebra courses in a state virtual school in the Midwestern US region during 2007-2008 participated in this study. Student final scores on these courses were collected using tests administered at the end of semester in the virtual school courses. The hierarchical linear modelling technique was used for data analysis to account for the influence of school characteristics on student final scores. The results show these factors have different influences on student final scores in different algebra courses. The discussion of the findings addresses the implications for teaching.

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Section: Participation In Online Academic Activitiesmentioning

confidence: 91%

Section: Conclusion and Future Studymentioning

confidence: 94%

Section: Open Learning 157mentioning

confidence: 96%

See 1 more Smart Citation

Factors influencing student academic performance in online high school algebra

Liu

Cavanaugh

2012

Open Learning: The Journal of Open, Distance and e-Learning

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“…A number of important quantitative studies have been done previously in the particular context of teaching Sociology [28][29][30][31][32]. These studies-differing from the one presented herein-used quantitative indicators such as course grade to measure learning outcomes.…”

Section: Previous Studies In the Context Of Teaching Sociologymentioning

confidence: 99%

Learning Outcomes in an Introductory Sociology Course: The Role of Learning Approach, Socio-Demographic Characteristics, Group and Teacher Effects

Miskolczi

Rakovics

2018

Societies

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Abstract:The article discusses a study on learning outcomes in an introductory Sociology course in a higher education setting. A quantitative model similar to education production functions is hypothesized. Independent variables include socio-demographic and psychological ones, as well as others pertaining to the learning environment. Learning is measured with the binary categories of "deep" and "surface" outcomes, which are qualitatively different, and are based on the comparison of mind maps drawn by students at the beginning and end of their first semester. Questionnaire data was collected from 264 first-year students of a Social Science Faculty. Significant effects on learning outcome are found for family background, major area of study, and teacher's gender.

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“…Concurrently, there has been increased pressure on post-secondary institutions to provide this education with budgets that have not kept up with the rising costs of providing such an education. These trends, combined with increased student diversity, leave "educators searching for new and effective teaching modalities that are time-and cost-efficient" (Dietz, 2002;p. 80).…”

Section: Changes To the Traditional Classroom Idea Of Teachingmentioning

confidence: 99%

The Effect of Data Analysis Modules in the Introductory Sociology Course: Lessons for the Social Sciences

Dietz

2006

Innov High Educ

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This article offers an evaluation of the implementation of the American Sociological Association's Integrating Data Analysis Project in a large introductory sociology course. This project was designed following an examination of the curricula of 13 disciplines that revealed that sociology failed to integrate empirical, quantitative literacy components throughout the undergraduate curriculum. Thus, efforts to introduce students to data analysis early and often were established as a best practice in the discipline. Results revealed that the students found the modules helped them understand the empirical nature of sociology. The students expressed an interest in participating in future research projects in sociology and/or other disciplines. They were not overly anxious about the quantitative literacy components of the course. Including on-line data analysis strategies using publicly available data and complimentary software represent cost and time-effective methods of introducing quantitative literacy into the social science classroom. Many social and behavioral sciences other than sociology have also discovered that their students lack a clear understanding of the relationship between empirical research and substantive topics within the discipline. Consequently, the lessons learned from the efforts of the ASA could be applied across many disciplines to form a more cohesive curriculum for many disciplines.

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Predictors of Success in Large Enrollment Introductory Courses: An Examination of the Impact of Learning Communities and Virtual Learning Resources on Student Success in an Introductory Level Sociology Course

Cited by 29 publications

References 5 publications

Factors influencing student academic performance in online high school algebra

Factors influencing student academic performance in online high school algebra

Learning Outcomes in an Introductory Sociology Course: The Role of Learning Approach, Socio-Demographic Characteristics, Group and Teacher Effects

The Effect of Data Analysis Modules in the Introductory Sociology Course: Lessons for the Social Sciences

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