Why Choose Online Learning: Relationship of Existing Factors and Chronobiology

Abstract

Existing research on choice of online learning utilized factors such as perceived level of control, independence, and satisfaction, yet the relationship among these factors is under-researched. Due to the value of “learning anytime,” biological factors underlying “choice of time” might provide additional insights. This article presents findings of a study with two aims: (1) investigating the relationship between previously described factors; and (2) researching the impact of a different theoretical framework, chronobiology, to provide insights in students' choices for online learning. Our research with traditional students taking online courses shows a statistically significant correlation between students' perceived independence, level of control, and satisfaction. Although there is no statistical significance between the three factors and the new factor of chronobiology, we found statistically significant results between students' chronotype and their choice of learning time for online classes. Implications and limitations are discussed.

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References

Allen

I. E.

Seaman

(2010). Learning on demand: Online education in the United States, 2009. Retrieved from http://sloanconsortium.org/publications/survey/pdf/learningondemand.pdf

Anderson

(Ed.). (2008). The theory and practice of online learning. AU Press: Athabasca University.

Artino

(2007). Online military training: Using a social cognitive view of motivation and self-regulation to understand students' satisfaction, perceived learning, and choice. Quarterly Review of Distance Education, 8(3), 191–202.

Artino

(2008a). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24(3), 260–270.

Artino

(2008b). Promoting academic motivation and self-regulation: Practical guidelines for online instructors. TechTrends, 52(3), 37–45.

Artino

A. R.

Stephens

J. M.

(2009). Beyond grades in online learning: Adaptive profiles of academic self-regulation among Naval Academy undergraduates. Journal of Advanced Academics, 20, 568–601.

Bernard

R. M.

Abrami

P. C.

Lou

Borokhovski

Wade

Wozney

(2004). How does distance education compare to classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379–439.

Bray

Aoki

Dlugosh

(2008). Predictors of learning satisfaction in Japanese online distance learners. International Review of Research in Online Distance Learning, 9(3). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/525/1153

Butler

Pinto-Zipp

(2005–2006). Students' learning styles and their preferences for online instructional methods. Journal of Educational Technology Systems, 34(2), 199–221.

10.

Callan

(1995). The potential effects of chronobiology on taking the Scholastic Aptitude Test. The Clearing House, 68(3), 174.

11.

DeBourgh

G. A.

(1999). Technology is the tool, teaching is the task: Student satisfaction in distance learning. In Price

(Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference, 1999 (pp. 131–137). Chesapeake, VA: AACE. Retrieved from http://www.editlib.org/p/7521

12.

Dunn

Primavera

Sinatra

Virostko

(2010). A timely solution: Effects of chronobiology on achievement and behavior. The Clearing House, 61(1), 5–8.

13.

Dutton

Perry

(2002). How do online students differ from lecture students? Journal of Asynchronous Learning Networks, 6(1). Retrieved from http://uwf.edu/atc/Guide/PDFs/how_online_students_differ.pdf

14.

Frankola

(2001). Why online learners dropout? Workforce, 53–63.

15.

Giannotti

Cortesi

Sebastiani

Ottaviano

(2002). Circadian preference, sleep and daytime behaviour in adolescence. Journal of Sleep Research, 11(3), 191–199.

16.

Griggs

S. A.

(1980). Chronobiology: Implications for learning and scheduling. The Learning Styles Network Newsletter, 1(3), 5.

17.

Guernsey

(1998). Distance education for the not-so-distant. The Chronicle of Higher Education, 44, A29–A30.

18.

Johnson

S. D.

Aragon

S. R.

Shaik

Palma-Rivas

(2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of Interactive Learning Research, 11, 29–49.

19.

Jovanovski

Bassili

(2007). The relationship between morningness-eveningness preference and online learning. Biological Rhythm Research, 38(5), 355–365.

20.

Katz

Y. J.

(2002). Attitudes affecting college students preferences for distance learning. Journal of Computer Assisted Learning, 18, 2–9.

21.

Klesius

J. P.

Homan

Thompson

(1997). Distance education compared to traditional instruction: The students' view. International Journal of Instructional Media, 24(3), 207–221.

22.

Kühnle

(2006). Quantitative analysis of human chronotypes. Dissertation, LMU München: Fakultät für Biologie. Retrieved from http://edoc.ub.uni-muenchen.de/5168/

23.

Kvavik

R. B.

Caruso

J. B.

(2005). ECAR study of students and information technology, 2005: Convenience, connection, control, and learning. Boulder, CO: Educause Center for Applied Research.

24.

Lim

D. H.

Kim

H. J.

(2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31(4), 423–439.

25.

Lim

Morris

(2005). The effect of flexible learning delivery format on online learners' learning, application, and instructional perception. Journal of Educational Technology Systems, 33(4), 385–397.

26.

Lynch

(1981). An analysis of the relationships among academic achievement, attendance, and the individual learning style time preferences of eleventh and twelfth grade students identified as initial or chronic truants in a suburban New York school district. Ph.D. dissertation, St. John's University, New York. Dissertation Abstracts International 42, 1880A.

27.

McFarland

Hamilton

(2005). Factors affecting student performance and satisfaction: Online versus traditional course delivery. Journal of Computer Information Systems, 46(2), 25–32.

28.

Mitru

Millrood

D. L.

Mateika

J. H.

(2002). The impact of sleep on learning and behavior in adolescents. Teacher College Record, 104(4), 704–726.

29.

National Center for Education Statistics. (2008). The condition of education 2008. Retrieved from http://nces.ed.gov/pubs2008/2008031.pdf

30.

Newby

T. J.

Stepich

D. A.

Lehman

J. D.

Russell

J. D.

(2006). Educational technology for teaching and learning. Upper Saddle River, NJ: Pearson Education.

31.

O'Malley

McCraw

(1999). Students perceptions of distance learning, online learning and the traditional classroom. Online Journal of Distance Learning Administration, 2(4). Retrieved from http://www.westga.edu/∼distance/omalley24.html

32.

Petrides

L. A.

(2002). Web-based technologies for distributed (or distance) learning: Creating learning-centered educational experiences in the higher education classroom. International Journal of Instructional Media, 29, 69–77.

33.

Piccoli

Ahmad

Ives

(2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25(4), 401–426.

34.

Pintrich

P. R.

Smith

Garcia

McKeachie

(1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). The University of Michigan, Ann Arbor, MI.

35.

Randler

Frech

(2006). Correlation between morningness-eveningness and final school leaving exams. Biological Rhythm Research, 37, 233–239.

36.

Roblyer

M. D.

(2000). Is choice important in distance learning? A study of student motives for taking internet-based courses at the high school and community college levels. Journal of Research on Computing in Education, 32(1), 157–171.

37.

Roblyer

M. D.

Wiencke

(2003). Design and use of a rubric to assess and encourage interactive qualities in distance courses. The American Journal of Distance Education, 17(2), 77–98.

38.

Rodriguez

M. C.

Ooms

Montanez

Yan

Y. L.

(2005). Perceptions of online learning quality given comfort with technology, motivation to learn technology skills, satisfaction, & online learning experience. Paper presented at the annual meeting of the American Educational Research Association, Montreal, Canada. Retrieved February 22, 2010 from edmeasurement.net

39.

Roenneberg

Wirz-Justice

Merrow

(2003). Life between clocks: Daily temporal patterns of human chronotypes. Journal of Biological Rhythms, 18(1), 80–90.

40.

Roenneberg

Kuehnle

Pramstaller

P. P.

Ricken

Havel

Guth

(2004). A marker for the end of adolescence. Current Biology, 14(24), R1038–R1039.

41.

Roenneberg

Kuehnle

Juda

Kantermann

Allebrandt

Gordijn

(2007). Epidemiology of the human circadian clock. Sleep Medicine Reviews, 11(6), 429–438.

42.

Sahin

Shelley

(2008). Considering students' perceptions: The distance education student satisfaction model. Educational Technology & Society, 11(3), 216–223.

43.

Sankaran

Bui

(2000). Effect of student attitude to course format on learning performance: An empirical study in web vs. lecture instruction. Journal of Instructional Psychology, 27(1), 66–73.

44.

Schrum

(2002). Oh, what wonders you will see: Distance education past, present, and future. Learning and Leading with Technology, 30, 7–13.

45.

Stokes

S. P.

(2003). Temperament, learning styles, and demographic predictors of college student satisfaction in a digital learning environment. Paper presented at the annual meeting of the Mid-South Educational Research Association, Biloxi, MS. Retrieved February 22, 2010 from eric.ed.gov

46.

Sullivan

(2001). Gender differences and the online classroom: Male and female college students evaluate their experiences. Community College Journal of Research & Practice, 25, 805–818.

47.

Swan

Shea

Fredericksen

Pickete

A. M.

Pelz

W. E.

(2000). Course design factors influencing the success of learning. Paper presented at WebNet 2000 World Conference on the WWW and Internet Proceedings, San Antonio, TX. Retrieved February, 22, 2010 from editlib.org

48.

Tankova

Adan

Buela-Casal

(1994). Circadian typology and individual differences: A review. Personality and Individual Differences, 16(5), 671–684.

49.

Veleri

(2003, September). The genes sense time? A clock ticks inside us! Asian Student Medical Journal. Retrieved July 31, 2011 from http://asmj.netfirms.com/article1103.html

50.

Wang

A. Y.

Newlin

M. H.

(2000). Characteristics of students who enroll and succeed in psychology web-based courses. Journal of Educational Psychology, 92(1), 137–143.

51.

Westbrook

T. S.

(1999). Changes in student attitudes toward graduate instruction via web-based delivery. Journal of Continuing Higher Education, 47(2), 32–38.

52.

Wittmann

Dinich

Merrow

Roenneberg

(2006). Social jetlag: Misalignment of biological and social time. Chronobiology International, 23(1&2), 497–509.

53.

U.S. Congress, Office of Technology Assessment. (1991, September). Biological rhythms: Implications for the worker. Washington, DC: U.S. Government Printing Office.