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Attitudes and Achievement in a Self-Paced Blended Mathematics Course
article

## Phoebe Balentyne, Northern Illinois University, United States ; Mary Alice Varga, University of West Georgia, United States

Journal of Online Learning Research Volume 3, Number 1, ISSN 2374-1473 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA

## Abstract

Blended learning opportunities are expanding for K-12 students in public school settings. As these opportunities increase, researchers and educators seek to discover specific characteristics of the students who are most successful in blended learning environments. The purpose of this study was to investigate the relationship between students’ achievement and their attitudes in a self-paced blended mathematics course. A total of 23 high ability eighth grade students participated in the study by completing the Measures of Academic Progress Mathematics Test and the Attitudes Toward Mathematics Inventory to examine the relationship between achievement growth during the course and attitudes at the end of the course. Findings revealed a significant positive correlation between achievement growth and attitudes toward mathematics. Achievement growth was also significantly positively correlated individually with each of the four attitudinal factors studied: value, motivation, enjoyment, and self-confidence. Furthermore, there were significant positive correlations between each of the individual attitudinal factors and overall attitudes toward mathematics. This research demonstrates that high ability students with the most positive attitudes toward mathematics may be more successful in self-paced blended mathematics courses. This is an important step in discovering which students are best suited for this learning environment.

## Citation

Balentyne, P. & Varga, M.A. (2017). Attitudes and Achievement in a Self-Paced Blended Mathematics Course. Journal of Online Learning Research, 3(1), 55-72. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved February 26, 2021 from https://www.learntechlib.org/primary/p/173313/.

© 2017 Association for the Advancement of Computing in Education (AACE)

## References

View References & Citations Map- Balentyne, P., & Varga, M.A. (2016). The effects of self-paced blended learning of mathematics. Journal of Computers in Mathematics and Science Teaching, 35(3), 201223.
- Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117-148.
- Bottge, B.A., Ma, X., Gassaway, L., Toland, M.D., Butler, M., & Cho, S.-J. (2014). Effects of blended instructional models on math performance. Exceptional Children, 80(4), 423-437. Doi:10.1177/0014402914527240
- Brown, J.L.M. (2012). Online learning: A comparison of web-based and land-based courses. Quarterly Review of Distance Education, 13(1), 39-42. Retrieved from http://www.infoagepub.com/quarterly-review-of-distance-education.html
- Creswell, J.W. (2015). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. (5th ed.). Boston: Pearson.
- Deshler, J., & Fuller, E. (2016). The effects of migration to a blended self-paced format for a remedial pre-college algebra mathematics course. Journal of Computers in Mathematics and Science Teaching, 35(2), 114-129. Retrieved from http://www.aace.org/pubs/jcmst/
- Edwards, C., & Rule, A. (2013). Attitudes of middle school students: Learning online compared to face to face. Journal of Computers in Mathematics and Science Teaching, 32(1), 49-66. Retrieved from http://www.aace.org/pubs/jcmst/ Edwards, C.M., Rule, A.C., & Boody, R.B. (2013). Comparison of face-to-face and online mathematics learning of sixth graders. Journal of Computers in Mathematics and Science Teaching, 32(1), 25-47. Retrieved from http://www.aace.org/pubs/
- Headden, S. (2013). The promise of personalized learning. Education Next, 13(4), 14-20. Retrieved from http://educationnext.org/the-promise-of-personalized-learning/ Horn, M.B., & Staker, H. (2011). The rise of K-12 blended learning. San Mateo, CA: Innosight Institute. Retrieved from http://www.christenseninstitute.org
- Howley, A., Rhodes, M., & Beall, J. (2009). Challenges facing rural schools: Implications for gifted students. Journal for the Education of the Gifted, 32(4), 515-536. Retrieved from http://www.sagepub.com/journals/Journal202068/ Kesici, S., & Erdogan, A. (2010). Mathematics anxiety according to middle school students’ achievement motivation and social comparison. Education, 131(1), 54-63.
- Kim, C., Park, S.W., & Cozart, J. (2014). Affective and motivational factors of learning in online mathematics courses. British Journal of Educational Technology, 45(1), 171185.
- Northwest Evaluation Association. (2004, March). Reliability and validity estimates: NWEA achievement level tests and measures of academic progress. Lake Oswego, OR.
- Olszewski-Kubilius, P., & Corwith, S. (2010). Distance education: Where it started and where it stands for gifted children and their educators. Gifted Child Today, 34(3), 16-65. Retrieved from http://www.nagc.org/gct.aspx/ Queen, B., & Lewis, L. (2011). Distance education courses for public elementary and secondary school students: 2009-10 (NCES Report No. 2012-008). Retrieved from
- Sanderson, E., & Greenberger, R. (2011). Evaluating online programs through a gifted lens. Gifted Child Today, 34(3), 42-53. Retrieved from http://www.nagc.org/gct.aspx Skaalvik, E.M., Federici, R.A., & Klassen, R.M. (2015). Mathematics achievement and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129-136. Doi:10.1016/J.ijer.2015.06.008
- Staker, H., & Horn, M.B. (2012). Classifying K-12 blended learning. San Mateo, CA: Innosight Institute. Retrieved from http://www.christenseninstitute.org/ Tapia, M. (1996, November). The attitudes toward mathematics instrument. Paper presented at the annual meeting of the Mid-South Educational Research Association, Tuscaloosa, AL.
- Taylor, S., Clements, P., Heppen, J., Rickles, J., Sorensen, N., Walters, K., Allensworth, E., & Michelman, V. (2016). Getting back on track: The role of in-person instructional support for students taking online credit recovery (Report No. 2). Chicago, IL: The University of Chicago Consortium on School Research. Retrieved from http://www.air.org/ Tempelaar, D.T., Niculescu, A., Rienties, B., Gijselaers, W.H., and Giesbers, B. (2012). How achievement emotions impact students’ decisions for online learning, and
- Wang, S., McCall, M., Jiao, H., & Harris, G. (2013). Construct validity and measurement invariance of computerized adaptive testing: Application to Measures of Academic Progress (MAP) using confirmatory factor analysis. Journal of Educational and Developmental Psychology, 3(1), 88-100.
- Yoon, S.Y., & Gentry, M. (2009). Racial and ethnic representation in gifted programs: Current status of and implications for gifted Asian American students. Gifted Child

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