Near And Far Transfer On E-Learning Environments: The Role Of Semantic Encoding Strategies
Author(s):
Esra Telli (presenting / submitting)
Conference:
ECER 2017
Format:
Paper

Session Information

16 SES 02 B, ICT and Language Teaching and Semantic Encoding

Paper Session

Time:
2017-08-22
15:15-16:45
Room:
W4.21
Chair:
Julia Gerick

Contribution

Many educators claim that the aim of formal education is to transfer information from one context to another (Halpern, 1998). Transfer is about how previous learning actions effect learning today and in the future and how the learning of the past and today are adapted to similar and new situations (Haskell, 2000). Although it is a proven fact that school life provides individuals some basic information and skills with different methods such as writing, reading and questioning and increases the intelligence of individuals, it is emphasized that it is insufficient in transfer support. Standard tests made on transfer and laboratory conflictions demonstrate that learning transfer is difficult (NSF, 2002).  This has led the researchers to understand the transfer process (Cheng, & Hamspon, 2007).

Studies on transfer increase day by day and the scope expands.Experimental studies on transfer were started in the beginning of 20th century (Judd, 1908; Thorndike & Woodworth, 1901). Thorndike supported that transfer occurs in identical situations. According to Skinner (1953), transfer includes the generalization of reactions between two distinguishing effects. After the cognitive revolution, mental symbolic presentation concept was started to be used instead of similar qualities concept (Lobato, 2006). Schunk (2009) emphasized that transfer is a very important element for learning, generally including complex cognitive operations. Cognitive concepts covered in learning emphasize the complexity of transfer operation (Phye, 2001). Although the transfer of simple level skills can be made automatically, many transfers require high level cognitive skills. Transfer is a basic concept in learning in terms of both the process and the result. It helps learning by making information receiving, storage, processing and preservation stages easier. 

With the transfer of studies for the development of learning-teaching process into this area with the increasing of information about human cognition, the analysis of transfer of learning in light of cognitive data has become necessary. Gick and Holyoak (1980) stated that transfer takes place when the students match a new situation they come across with schemes coded before and find suitable solutions. So transfer depends completely on information recorded and encoded before. Transfer takes place when information and productions are connected to different contents in long-term memory. In this context, it is important to consider how transfer performance, information coding was carried out.

As many studies were made and are still made on learning transfer in traditional learning platforms, transferability of learning both in e-learning and e-learning platforms has revealed a new research area with the reflection of technological developments on learning platforms. Bonk and Reynolds (1997) stated that these platforms should be organized in a way to create a connection between past and new learning of individuals in order to provide high-level of thinking on web platform.   There are two restrictions making the transfer in e-learning platforms more difficult. The first is lack of guidance in to make learning transfer and the second is lack of satisfactory care for platform design. Factors effecting learning transfer in platform design should be considered to be successful in e-learning (Chan, Tsai, & Huang, 2006; Chen, Huang, & Chu., 2005; Kabassi & Virvou, 2003; Zhu, 2007).

The aim of this research is to examine the effect of semantic encoding strategies training to be provided in e-learning platform on near and far transfer performances of the students. There is a close connection between recalling information from long-term memory and encoding. Transfer of learning is effected both by recalling and semantic encoding performance. As the effect of encoding on transfer performance is examined for this reason in the research, recalling performance was controlled and individuals with similar recalling performances were included in the research. 

Method

The research was performed on Hacettepe University CEIT students. As recalling performances would be controlled in order to determine the students participating in the research, individuals in the same performance group were studied. In order to determine the individuals with a similar recalling level, 105 students were given enhanced cued recall test. This test was developed by Grober, et al (1988). At the end of the implementation, lower and upper groups 1 standard deviation away from average formed the groups with "low" and "high" level recalling performance and the individuals among these groups formed the groups with "medium level" recalling performance. 75 students with medium level of recalling performance were chosen for this research. Research data were gathered with a transfer test containing 18 multiple-choice items (9 near transfer test, 9 far transfer test) developed and validity-reliability checked by researchers. First of all, forming a two-section transfer test consisting of 29 items to measure near and far transfer, expert opinion was taken on content validity. Experts were asked to rate transfer levels of multiple choice items. Cohen KAPPA coefficient was calculated for comparative match among experts as .819. 6 questions the experts couldn't agree on were removed from the test. After that, the pilot test was applied to 162 students in an another university. Structural validity of the test was controlled. Factor analysis was made using tetrachoric correlation in order to test unidimensionality for near transfer and far transfer tests. 5 items were removed in total and there were 18 final test questions. The research was performed by experimental design. Dependent variables of the research were near and far transfer performances. Independent variable was strategy training on encoding. Also recalling performance was included in the research as a control variable.Before the treatment, students took the pretest on flexible instructional design models and were randomly divided into three different groups. Experimental group 1 received training on semantic encoding strategies and then training instructional design models on e-learning environment that integrated with these strategies, Experimental group 2 received encoding strategies training and then instructional design models on e-learning environment that not integrated with strategies, Control group received training on instructional design models on e-learning environment that not integrated with strategies and didn't receive encoding strategies training. The treatment lasted three weeks. Posttest was applied right after the treatment. After 3 weeks retention test was applied.

Expected Outcomes

Data were analyzed by repeated measure ANOVA. Findings indicated that students’ near transfer performance significantly differs according to groups. Post-hoc test performed and it is found that there is a significant difference between experimental group 1 and experimental group 2, in favor of experimental group 1 (p<.05). Also there is a significant differences between experimental group 1 and control group in favor of experimental group 1 (p<.05). But there is no significant differences between experimental group 2 and control group. Findings indicated that students’ far transfer performance significantly differs according to groups. Post-hoc test performed and it is found that there is a significant difference between experimental group 1 and experimental group 2, in favor of experimental group 1 (p<.05). Also there is a significant differences between experimental group 1 and control group in favor of experimental group 1 (p<.05). But there is no significant differences between experimental group 2 and control group. Results of this research indicated that encoding strategy training is important for transfer of learning on e-learning environments. But it’s more effective when e-learning design integrated with encoding strategies. According the results, semantic encoding strategies should be integrated into the content when designing an e-learning environments and this may help owercome the weakness of e-learning.

References

Bonk, C. J., & Reynolds, T. H. (1997). Learner-centered web instruction for higher-order thinking, teamwork, and apprenticeship. In B. H. Khan (Ed.), Web-based instruction (pp. 167-178). Englewood Cliffs, NJ: Educational Technology Publications. Chan, H. G., Tsai, P. H., & Huang, T. Y. (2006). Web-based learning in a geometry course. Educational Technology & Society, 9 (2), 133-140. Cheng, E. W. L. & Hampson, I. (2008). Transfer of training: a review and new insights. International Journal of Management Reviews, 10, 327–41. Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306-355. Grober, E., Buschke, H., Crystal, H., Bang, S., & Dresner, R. (1988). Screening dementia by memory testing. Neurology, 38, 900–903. Halpern, D. F. (1998). Teaching critical thinking for transfer across domains. American Psychologist, 53(4), 449–455. Haskell, R. (2000). Transfer of Learning: Cognition, Instruction and Reasoning. San Diego: Academic Press. Judd, C.H. (1908). The relation of special training to general intelligence. Educational Review, 36, 28-42. Kabassi, K., & Virvou, M. (2003). Using Web services for personalised Web-based learning. Educational Technology & Society, 6 (3), 61-71. Lobato, J. (2006). Alternative Perspectives on the transfer of learning: History, issues, and challenges for future research. The Journal of the Learning Sciences, 15(4), 431–449. National Science Foundation. (2002). Transfer of Learning: Issues and Research Agenda. Phye, G.D. (2001). Problem-solving instruction and problem-solving transfer: The correspondence issue. Journal of Educational Psychology, 93(3),571-578. Schunk, D. H. (2009). Öğrenme Teorileri – Eğitimsel Bir Bakış (çev. ed. M. Şahin). Ankara: Nobel Yayın Dağıtım. Skinner, B. F. (1953). Science of Human Behavior. New York: Free Press. Thorndike, E. L.,& Woodworth, R. S. (1901). The influence of improvement in one mental function upon the efficiency of other functions. Psychological Review, 8, 247-261. Zhu, X. H. (2007). Extending the SCORM specification for references to the open content object. Educational Technology & Society, 10 (1), 248-264

Author Information

Esra Telli (presenting / submitting)
Erzincan University
ceit
Erzincan

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