Exploring The Influences on Cyber Education in a Bilingual Higher Institution

Simon Wong

Abstract


This paper presents the research study which explores the variables influencing the learning effectiveness of the students taking an online introductory information technology course in cyber education in a bilingual higher education institution in Hong Kong. These variables are: (1) student's English proficiency, (2) instructor's guidance in an online discussion forum and (3) peer students' collaboration in an online discussion forum. Correlation analysis was adopted to identify whether any of these variables could be potential factors on the students 'learning performance while multiple regression analysis was performed to explore the combined effect of these variables on the students' learning performance. Validity and reliability of this research study are highlighted in this paper. Finally, the research findings are discussed.

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Keywords


Cyber education; learning effectiveness; students' English proficiency; instructors' guidance; students' collaboration; online discussion forums;

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References


A. Hwangand J. B. Arbaugh, Seeking feedback in blended learning: competitive versus cooperative student attitudes and their links to learning outcomes, Journal of Computer Assisted Learning, 25 (3), 280-293, 2009.

A.B. Y. Wang and M. H. Newlin, Characteristics of students who enroll and succeed in psychology Web-classes, Journal of Educational Psychology, 92 (1), 137-143, 2000.

B. G. Tabachnick, and L. S. Fidell, Using Multivariate Statistics, 5th Edition, Boston: Pearson / Allyn and Bacon, 2007.

C. L. Aberson, D. E. Berger, M. R. Healy, D. J. Kyle and V. L. Romero, Evaluation of an interactive tutorial for teaching the central limit theorem, Teaching of Psychology, 27 (4), 289-292, 2000.

C. Stangor, Research Methods for the Behavioral Sciences, 4th Edition, Belmont: Wadsworth / Cengage Learning, 2011.

D. Y. F. Hoand J. A. Spinks, Multivariate prediction of academic performance by Hong Kong university students. Contemporary Educational Psychology, 10 (3), 249-259, 1985.

E. Babbie, The Basics of Social Research, Belmont: Wadsworth / Cengage Learning, 2014.

E. Fredericksen, A. Pickett, P. Shea, W. Pelzand K. Swan, Student satisfaction and perceived learning with on-line courses: principles and examples from the SUNY learning network, Journal of Asynchronous Learning Networks, 4 (2), 7-41, 2000.

Education Commission, Education Commission Report No. 6, Hong Kong: Government Printer, 1996.

Education Commission, Education Blueprint for the 21stCentury. Review of Academic System: Aims of Education, Hong Kong: Printing Department, 1999.

J. C. Nunnelly, Psychometric Theory, 2nd Edition, New York: McGraw Hill, 1978.

J. G. Graham, English language proficiency and the prediction of academic success, TESOL Quarterly, 21 (3), 505-521, 1987.

J. Lim, M. Kim, S. S. Chen and C. E. Ryder, An empirical investigation of student achievement and satisfaction in different learning environments, Journal of Instructional Psychology, 35 (2), 113-119, 2008.

J. Mercer, The challenges of insider research in educational institutions: wielding a double-edged sword and resolving delicate dilemmas, Oxford Review of Education, 33 (1), 1-17, 2007.

J. Pallant, SPSS: Survival Manual: A Step by Step Guide to Data Analysis using SPSS for Windows, 3rdEdition, New York: McGraw-Hill, 2007.

J. W. Creswell, Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research, 3rd Edition, Upper Saddle River: Pearson, 2008.

K. L. Chin, C. Bauerand V. Chang, The Use of Web-based Learning in Culturally Diverse Learning Environments, the 6thAustralian World Wide Web Conference, Cairns, Australia, 2000.

K. Swan, Virtual interaction: design factors affecting student satisfaction and perceived learning in asynchronous online courses, Distance Education, 22 (2), 306-331, 2001.

L. B. Christensen, R. B. Johnsonand L. Turner, Research Methods, Design and Analysis, 12th Edition, Upper Saddle River: Pearson, 2014.

L. J. Cronbach, Coefficient alpha and the internal structure of tests, Psychometrika, 16,297-334, 1951.

M. Gerber, S. Grundand G. Grote, Distributed collaboration activities in a blended learning scenario and the effects on learning performance, Journal of Computer Assisted Learning, 24 (3), 232-244, 2007.

M. Saunders, P. Lewisand A. Thornhill, Research Methods for Business Students, 5th Edition, New York: FT / Prentice Hall, 2009.

N. A. Weiss, Introductory Statistics, 9th Edition, Boston: Addison-Wesley / Pearson, 2012.

N. Li, D. Y. P. Leungand D. Kember, Medium of instruction in Hong Kong universities: the mis-match between espoused theory and theory in use, Higher Education Policy, 14, 293-312, 2001.

P. Cooper, Field relations and the problem of authenticity in researching participants' perceptions of teaching and learning in classrooms, British Educational Research Journal, 19 (4), 323-338, 1993.

R. A. Ellisand R. A. Calvo, Discontinuities in university student experiences of learning through discussions, British Journal of Educational Technology, 37 (1), 55-68, 2006.

R. F. DeVellis, Scale Development: Theory and Applications, 2ndEdition, Thousand Oaks: Sage, 2003.

R. K. Johnson, C. K. W. Shekand E. H. F. Law, Using English as the Medium of Instruction, Hong Kong: Longman, 1993.

R. Likert, A technique for the measurement of attitudes, Archives of Psychology, 140, 5-53, 1932.

S. Johnson, S. Aragon, N. Shaikand N. Palma-Rivas, Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments, Journal of Interactive Learning Research, 11 (1), 29-49 , 2000.

S. Wong, An Evaluation of Pre-university Students' Performance Studying On-line Education in an Introductory Information Technology Course, International Conference of Education, Research and Innovation, Madrid, Spain, 2008.

S. Wong, Factors Influencing On-line Learning: A Study Using Mixed Methods in a Hong Kong Higher Education Institution, Saarbrücken, Germany: LAMBERT Academic Publishing, 2012.

T. Z. Keith, Structural equation modeling in school psychology, in Reynolds, C.R. and Gutkin, T.B. (Eds.) The Handbook of School Psychology, 3rd Edition, New York: Wiley, 1999.

T. Z. Keith, Multiple Regression and Beyond, Boston: Pearson / Allyn and Bacon, 2006.


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International Journal of Informatics and Information Systems (IJIIS)

2579-7069 (Online)
Organized by Information System Department - Universitas Amikom Purwokerto - Indonesia, Laboratoire Signaux Et Systèmes (L2s) - Université Paris 13 - FranceAsosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) and Bright Publisher
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