Yıl 2018, Cilt 11, Sayı 4, Sayfalar 1003 - 1018 2018-10-24

A Systematic Review of Online Learning Researches in the Context of Individual Differences
Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme

Hale ILGAZ [1]

54 125

Online learning has been offering practical, efficient and effective solutions for reaching out big groups of learners in terms of learning and education. In these environments, where the participants have distinct properties, although the contents have been diversified, it has been represented with the assumption of ideal user. These environments consist many people who have very distinct properties from each other. Even if the presented content has been diversified, mostly it is designed for the ideal user. However, every person has some individual characteristics, which can be natal and acquired in time. These individual differences are important in order to provide effective learning experiences in learning environments. In this context when the e-learning studies analyzed it can be seen that there are several studies, which focused on individual differences. In these studies, the effects of the variables such as personal traits, cognitive characteristics, and prior learning experiences on individuals’ academic success, motivation, participation levels, and staying on system, and the relationships had been analyzed. The main objective of this study is conducting a systematic review with the aim of identifying which individual differences studied and their relationships with other variables between 2010-2017 years. In this context, researcher defined review criteria (keywords, selection criteria, method) and conducted review process. According to search results, 38 research articles have been included in this study. Prominent results show that cognitive differences have been worked less in comparison with the other variables in terms of individual differences perspective, while the most worked variables are demographic variables and personal traits. 

e-Öğrenme aynı anda büyük kitlelere ulaşmada, eğitim-öğretim faaliyetleri yürütmede etkili, hızlı ve verimli çözümler sunabilmektedir. Birbirinden farklı özelliklere sahip katılımcıların bulunduğu bu ortamlarda bireylere çeşitlendirilmiş olsa da ideal kullanıcı varsayımına göre içerik türleri sunulmaktadır. Oysaki her birey doğuştan getirdiği ve sonradan kazandığı bir takım özelliklere sahiptir. Bu bireysel farklılıklar da öğrenme ortamlarında etkili öğrenme deneyimleri sağlayabilmek adına önemlidir. Bu bağlamda alanyazın incelendiğinde de bireysel farklılıkları odağına alan birçok e-öğrenme çalışması olduğu görülmektedir. Kişilik özellikleri, bilişsel özellikler, geçmiş öğrenme deneyimleri gibi sıralanabilen bu değişkenlerin bireylerin akademik başarılarına, motivasyonlarına, katılım düzeylerine ve sistemde kalmalarına olan etkileri ve aralarındaki ilişkiler incelenmiştir. Bu çalışmanın temel amacı sistematik bir alanyazın taraması gerçekleştirilerek, 2010-2017 yılları arasında yayınlanan çalışmalara konu olan bireysel farklılıkların belirlenmesi ve bu farklılıkların hangi bağımlı değişkenlerle incelendiğinin ortaya konulmasıdır. Bu kapsamda belirlenen alanyazın tarama kriterlerine göre (anahtar kelimeler, seçim kriterleri, yöntem) ISI Web of Knowledge, Ebscohost, Scopus ve JSTOR veritabanlarında taramalar gerçekleştirilmiş olup 38 makale çalışmaya dahil edilmiştir. Öne çıkan bulgular bireysel farklılıklar bağlamında bilişsel özelliklerin diğer değişkenlere oranla daha az incelendiğini gösterirken en fazla incelenen değişkenlerin demografik değişkenler ve kişilik özellikleri oldukları bulunmuştur.
  • Accuray Research LLP. (2017). Global E-Learning Market Analysis & Trends - Industry Forecast to 2025. Retrieved from https://www.researchandmarkets. com/research/qgq5vf/global_elearning.
  • Bear, A. A. G. (2012). Technology, Learning, and Individual Differences. Journal of Adult Education, 41(2), 27-42.
  • Chen, S. Y., & Macredie, R. (2010). Web-based interaction: A review of three important human factors. International Journal of Information Management, 30(5), 379-387. doi:10.1016/j.ijinfomgt.2010.02.009
  • Cho, M.H., Demei, S., & Laffey, J. (2010). Relationships Between Self-Regulation and Social Experiences in Asynchronous Online Learning Environments. Journal of Interactive Learning Research, 21(3), 297-316.
  • Clay, M. N., Rowland, S., & Packard, A. (2009). Improving undergraduate online retention through gated advisement and redundant communication. Journal of College Student Retention: Research, Theory and Practice, 10(1), 93–102.
  • Clewley, N., Chen, S. Y., & Liu, X. (2011). Mining Learning Preferences in Web-based Instruction: Holists vs. Serialists. Educational Technology & Society, 14 (4), 266–277.
  • Deborah, L. J., Baskaran, R., & Kannan, A. (2014). Learning styles assessment and theoretical origin in an e-learning scenario: A survey. Artificial Intelligence Review, 42(4), 801–819.
  • Ekwunife-Orakwue, K. C. V., & Tian-Lih, T. (2014). The impact of transactional distance dialogic interactions on student learning outcomes in online and blended environments. Computers & Education, 78, 414-427. doi:10.1016/j. compedu.2014.06.011
  • Felder, R. M., & Silverman, L. K. (1988). Learning styles and teaching styles in engineering education. Engineering Education, 78(7), 674–681.
  • Ghorbani, F., & Montazer, G. A. (2015). E-learners' personality identifying using their network behaviors. Computers in Human Behavior, 51(PA), 42-52. doi:10.1016/j.chb.2015.04.043
  • Gökçearslan, Ş., & Alper, A. (2015). The effect of locus of control on learners' sense of community and academic success in the context of online learning communities. Internet and Higher Education, 27, 64-73. doi:10.1016/j.iheduc.2015.06.003
  • Granić, A., & Adams, R. (2011). User sensitive research in e-learning: Exploring the role of individual user characteristics. Universal Access in the Information Society, 10(3), 307-318. doi:10.1007/s10209-010-0207-7
  • Higgins, JPT, & Green, S. (2011). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration. Retrieved from http://handbook.cochrane.org.
  • Hsia, J. W., Chang, C. C., & Tseng, A. H. (2014). Effects of individuals' locus of control and computer self-efficacy on their e-learning acceptance in high-tech companies. Behaviour and Information Technology, 33(1), 51-64. doi:10.1080/0144929X.2012.702284
  • Ivankova, N. V., & Stick, S. L. (2007). Students’ persistence in a distributed doctoral program in educational leadership in higher education: A mixed methods study. Research in Higher Education, 48(1), 93–135.
  • Jashapara, A., & Tai, W. C. (2011). Knowledge Mobilization Through E-Learning Systems: Understanding the Mediating Roles of Self-Efficacy and Anxiety on Perceptions of Ease of Use. Information Systems Management, 28(1), 71-83. doi:10.1080/10580530.2011.536115
  • Jraidi, I., & Frasson, C. (2013). Student’s Uncertainty Modeling through a Multimodal Sensor-Based Approach. Educational Technology & Society, 16 (1), 219–230.
  • Kanar, A. M., & Bell, B. S. (2013). Guiding Learners through Technology-Based Instruction: The Effects of Adaptive Guidance Design and Individual Differences on
  • Learning over Time. Journal of Educational Psychology, 105(4), 1067-1081.
  • Keller, H., & Karau, S. J. (2013). The importance of personality in students' perceptions of the online learning experience. Computers in Human Behavior, 29(6), 2494-2500. doi:10.1016/j.chb.2013.06.007
  • Kirschner, P. A. & van Merriënboer, J.J.G. (2013). Do Learners Really Know Best? Urban Legends in Education. Educational Psychologist, 48(3), 169-183.doi: 10.1080/00461520.2013.804395
  • Kolb, D. A. (1984). Experiential learning. Englewood Cliffs, NJ: Prentice Hall.
  • Lee, Y., & Choi, J. (2011). A review of online course dropout research: implications for practice and future research. Educational Technology Research and Development, 59(5), 593-618. doi:10.1007/s11423-010-9177-y
  • Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185-204. doi:10.1016/j.compedu.2004.12.004
  • Lu, H.-P., & Chiou, M.-J. (2010). The impact of individual differences on e-learning system satisfaction: A contingency approach. British Journal of Educational Technology, 41(2), 307-323. doi:10.1111/j.1467-8535.2009.00937.x
  • McCrae, R. R., & Costa, P. T. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52, 81-90.
  • McCrae, R. R. and John, O. P. (1992), An Introduction to the Five-Factor Model and Its Applications. Journal of Personality, 60, 175–215. doi:10.1111/j.1467-6494.1992.tb00970.x
  • Nawrot, I., & Doucet, A. (2014). Building engagement for MOOC students: introducing support for time management on online learning platforms. Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, 1077-1082.
  • Orvis, K. A., Brusso, R. C., Wasserman, M. E., & Fisher, S. L. (2011). E-nabled for E-Learning? The Moderating Role of Personality in Determining the Optimal Degree of Learner Control in an E-Learning Environment. Human Performance, 24(1), 60-78. doi:10.1080/08959285.2010.530633
  • Park, J.Y., & Choi, H.J. (2009). Factors Influencing Adult Learners' Decision to Drop Out or Persist in Online Learning. Journal of Educational Technology & Society, 12(4), 207-217.
  • Poll, K., Widen, J., & Weller, S. (2014). Six instructional best practices for online engagement and retention. Journal of Online Doctoral Education, 1(1), 56- 72
  • Price, L. (2004). Individual Differences in Learning: Cognitive control, cognitive style, and learning style. Educational Psychology, 24(5), 681-698. doi: 10.1080/0144341042000262971
  • Raes, A., Schellens, T., De Wever, B., & Vanderhoven, E. (2012). Scaffolding information problem solving in web-based collaborative inquiry learning. Computers & Education, 59(1), 82-94. doi:10.1016/j.compedu.2011.11.010
  • Randler, C., Horzum, M. B., & Vollmer, C. (2014). The Influence of Personality and Chronotype on Distance Learning Willingness and Anxiety among Vocational High School Students in Turkey. International Review of Research in Open and Distance Learning, 15(6), 93-110.
  • Ren, Y., Dai, Z.-x., Zhao, X.-h., Fei, M.-m., & Gan, W.-t. (2017). Exploring an on-line course applicability assessment to assist learners in course selection and learning effectiveness improving in e-learning. Learning & Individual Differences, 60, 56-62. doi:10.1016/j.lindif.2017.09.002
  • Rovai, A. P. (2001). Classroom community at a distance: A comparative analysis of two ALN-based university programs. The Internet and Higher Education, 4(2), 105-118.
  • Sanchez-Franco, M. J., Peral-Peral, B., & Villarejo-Ramos, A. F. (2014). Users' intrinsic and extrinsic drivers to use a web-based educational environment. Computers & Education, 74, 81-97. doi:10.1016/j.compedu.2014.02.001
  • Schaeffer, C. E., & Konetes, G. D. (2010). Impact of learner engagement on attrition rates and student success in online learning. International Journal of Instructional Technology & Distance Learning, 7(5), 3-9.
  • Sun, J. C.-Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2). 191–204. doi:10.1111/j.1467-8535.2010.01157.x
  • Tempelaar, D. T., Niculescu, A., Rienties, B., Gijselaers, W. H., & Giesbers, B. (2012). How Achievement Emotions Impact Students' Decisions for Online Learning, and What Precedes Those Emotions. Internet and Higher Education, 15(3), 161-169.
  • Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox, P. W. (1977). Field-dependent and field-independent cognitive styles and their educational implications. Review of Educational Research, 47, 1-64.
Birincil Dil tr
Konular Eğitim, Bilimsel Disiplinler
Dergi Bölümü Makaleler
Yazarlar

Orcid: 0000-0001-7011-5354
Yazar: Hale ILGAZ (Sorumlu Yazar)
Kurum: Ankara Üniversitesi Uzaktan Eğitim Merkezi
Ülke: Turkey


Bibtex @derleme { akukeg407289, journal = {Kuramsal Eğitimbilim Dergisi}, issn = {1308-1659}, eissn = {1308-1659}, address = {Afyon Kocatepe Üniversitesi}, year = {2018}, volume = {11}, pages = {1003 - 1018}, doi = {10.30831/akukeg.407289}, title = {Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme}, key = {cite}, author = {ILGAZ, Hale} }
APA ILGAZ, H . (2018). Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme. Kuramsal Eğitimbilim Dergisi, 11 (4), 1003-1018. DOI: 10.30831/akukeg.407289
MLA ILGAZ, H . "Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme". Kuramsal Eğitimbilim Dergisi 11 (2018): 1003-1018 <http://dergipark.gov.tr/akukeg/issue/38993/407289>
Chicago ILGAZ, H . "Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme". Kuramsal Eğitimbilim Dergisi 11 (2018): 1003-1018
RIS TY - JOUR T1 - Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme AU - Hale ILGAZ Y1 - 2018 PY - 2018 N1 - doi: 10.30831/akukeg.407289 DO - 10.30831/akukeg.407289 T2 - Kuramsal Eğitimbilim Dergisi JF - Journal JO - JOR SP - 1003 EP - 1018 VL - 11 IS - 4 SN - 1308-1659-1308-1659 M3 - doi: 10.30831/akukeg.407289 UR - http://dx.doi.org/10.30831/akukeg.407289 Y2 - 2018 ER -
EndNote %0 Kuramsal Eğitimbilim Dergisi Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme %A Hale ILGAZ %T Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme %D 2018 %J Kuramsal Eğitimbilim Dergisi %P 1308-1659-1308-1659 %V 11 %N 4 %R doi: 10.30831/akukeg.407289 %U 10.30831/akukeg.407289
ISNAD ILGAZ, Hale . "Bireysel Farklılıklar Kapsamında Çevrimiçi Öğrenme Araştırmalarına İlişkin Sistematik Bir Derleme". Kuramsal Eğitimbilim Dergisi 11 / 4 (Ekim 2018): 1003-1018. http://dx.doi.org/10.30831/akukeg.407289