Lexical access, knowledge transfer and meaningful learning of scientific terminology via an etymological approach

Year 2014, Volume: 3 Issue: 2, 1 - 12, 01.12.2014

Adam Oliver Brown

https://doi.org/10.20876/ijobed.92616

Cited By: 3

Abstract

This study aims to illustrate whether or not students of a second-year introductory Zoology course who were taught their course terminology using an etymological approach would show improved learning on a number of metrics of student performance. Undergraduate students of any academic discipline are challenged by the learning of its specialized language, especially in the terminology rich fields of scientific study. A common approach among students towards learning the terminology is via rote memorization, often with little success. Studies in language learning have shown that learning scaffolds that involve a morphological breakdown of new words into their morpheme units allows for improved lexical access, as well as greater knowledge retention and transfer abilities to other words in the same morpheme families. The scientific lexicon is mostly made up of root morphemes and is auto-descriptive, therefore, by using an etymological approach while learning new scientific terminology, there are two advantages over rote techniques: firstly to have a learning scaffold that may allow students to integrate unfamiliar terminology into their personal lexical repertoires and secondly, to have the ability to infer meaning of the terms’ properties with respect to their scientific contexts. These contributions may constitute a more meaningful student learning experience than factual intake and regurgitation and also they are allowing for metacognitive processing and conceptual linkage to the structure and/or function properties of terminology in their specialized scientific disciplines. This study adds to the growing body of teacher-led instructional learning resources for specialized vocabulary components of effective specialized scientific language learning at the University undergraduate level

Keywords

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References

• Ahlberg, P.E. and Milner, A.R. (1994). The origin and early diversification of tetrapods. Nature, 368, 507-514.
• Anderson, L.W. and Krathwohl, D.R. (2001). A taxonomy for learning, teaching and assessing: a revision of Bloom’s Taxonomy of Educational Objectives. New York: Longman.
• Angelo, T.A. (1996). Relating Exemplary Teaching to Student Learning. New Directions for Teaching and Learning, 65, 57-64.
• Balota, D.A., M.J. Cortese, S.D. Sergent-Marshall, D.H. Spieler and M.J. Yap. (2004). Visual Word Recognition of Single-Syllable Words. Journal of Experimental Psychology, 133, 283-316.
• Baugh, A.C. and Cable, T. (1993). A History of the English Language (4th ed.). New Jersey : Prentice-Hall.
• Brahler, C.J. and Walker, D. (2008). Learning scientific and medical terminology with a mnemonic strategy using an illogical association technique. Advances in Physiology Education, 32, 219-224.
• Briscoe, C. and LaMaster, S.U. (1991). Meaningful learning in college Biology through concept mapping. The American Biology Teacher, 53, 214-219.
• Bruer, J.T. (1993). Intelligent Novices: Knowing how to learn. In: Schools for thought: a science of learning in the classroom (pp. 51-79). Cambridge : MIT press.
• Carlisle, J.F. (2000). Awareness of the structure and meaning of morphologically complex words: Impacts on reading. Reading and Writing, 12, 169-190.
• Carlisle, J.F. (2010). Effects of instruction in morphological awareness on literacy achievement: an integrative review. Reading Research Quarterly, 45, 464-487.
• Carlisle, J.F. and Fleming, J. (2003). Lexical processing of morphologically complex words in the elementary years. Scientific Studies of Reading, 7, 239-253.
• Carpenter, F. (1956). The effect of different learning methods on concept formation. Science Education, 40, 282- 285.
• Chamot, A.U. (2004). Issues in Language Learning Strategy Research and Teaching. Electronic Journal of Foreign Language Teaching, 1, 14-26.
• Chickering, A.W. and Gamson, Z.F. (1987). Seven principles for good practice in undergraduate education. American Association of Higher Education Bulletin, 39, 3-7.
• Cohen, M.S.R. (1967). Histoire d'une langue, le français (des lointaines origines à nos jours). Paris, Éditions sociales.
• Cohen, M.D. (1991). Individual learning and organizational routine: emerging connections. Organization Science, 2, 135-139.
• Drury, N.E., Powell-Smith, E. and McKeever, J.A. (2002). Medical practitioners’ knowledge of Latin. Medical Education, 36, 1175.
• Fang, Z. (2006). The language demands of Science reading in middle school. International Journal of Science Education, 28, 491-520.
• Flavell, J.H. (1979). Metacognition and cognitive monitoring: a new area of cognitive-developmental inquiry. American Psychologist, 34, 906-911.
• Goh, C. (2008). Metacognitive Instruction for Second Language Listening Development: Theory, Practice and Research Implications. RELC Journal, 39, 188-213.
• Haag, L. and E. Stern. (2003). In Search of the Benefits of Learning Latin. Journal of Educational Psychology, 95, 174-178.
• Hand, B. and V. Prain. (2006). Moving from Border Crossing to Convergence of Perspectives in Language and Science Literacy Research and Practice. International Journal of Science Education, 28, 101-107.
• Hauk, O., F. Pulvermüller, M. Ford, W.D. Marslen-Wilson and M.H. Davis. (2009). Can I have a Quick Word? Early Electrophysiological Manifestations of Psycholinguistic Processes Revealed by Event-Related Regression Analysis of the EEG. Biological Psychology, 80, 64-74.
• Heinrich, D. (1992). Technical words in science education: terminology. The Australian Science Teachers Journal, 38, 57-58.
• Henry, M.K. (1993). Morphological structure: Latin and Greek roots and affixes as upper grade code strategies. Reading and Writing, 5, 227-241.
• Hogben, L. (1969). The vocabulary of science. New York : Stein & Day.
• Kuh, G.D. and Vesper, N. (1997). A Comparison of Student Experiences with Good Practices in Undergraduate Education Between 1990 and 1994. The Review of Higher Education, 21, 43-61.
• Kuh, G.D., Pace, C.R. and Vesper, N. (1997). The development of process indicators to estimate student gains associated with good practices in undergraduate education. Research in Higher Education, 38, 435-454.
• Laing, J., Sawyer, R. and Noble, J. (1987). Accuracy of Self-Reported Activities and Accomplishments of College- Bound Students. ACT Research Report Series, 87, 1-20.
• Lidbury, B. and F. Zhang. (2008). Comprehension of Scientific Language as a Strategy to Enhance Learning and Engagement for Molecular Biology Students. Australian Biochemist, 39, 10-13.
• Locke, D. (1992). Science as Writing. New Haven : Yale University Press.
• Marslen-Wilson, W., Tyler, L.K., Waksler, R. and Older, L. (1994). Morphology and meaning in the English mental lexicon. Psychological Review, 101, 3-33.
• Mayer, R.E. (2002). Rote versus meaningful learning. Theory into Practice, 41, 226-232.
• Miller, S.A., Perrotti, W., Silverthorn, D.U., Dalley, A.F. and Rarey, K.E. (2002). From college to clinic: reasoning over memorization is key for understanding anatomy. The Anatomical Record (New Anat.), 269, 69-80.
• Morton, J. (1969). Interaction of information in word recognition. Psychology Review, 76, 165-178.
• Murrell, G.A. and Morton, J. (1974). Word recognition and morphemic structure. Journal of Experimental Psychology. 102, 963-968.
• Nagy, W. and Townshend, D. (2012). Words as tools: Learning academic vocabulary as language acquisition. Reading Research Quarterly, 47, 91-108.
• Nosratinia, M., M. Saveiy and A. Zaker. (2014). EFL Learners’ Self-efficacy, Metacognitive Awareness, and Use of Language Learning Strategies: How Are They Associated? Theory and Practice in Language Studies, 4, 1080-1092.
• Pexman, P.M., I.S. Hargreaves, P.D. Siakaluk, G.E. Bodner and J. Pope. (2008). There are Many Ways to be Rich: Effects of Three Measures of Semantic Richness on Visual Word Recognition. Psychonomic Bulletin & Review, 15, 161-167.
• Posner, H.B. (1996). Teaching Introductory Cell & Molecular Biology: A Historical & Empirical Approach. The American Biology Teacher, 58, 272-274.
• Pike, G.R. (1995). The Relationship Between Self-Reports of College Experiences and Achievement Test Scores. Research in Higher Education, 36, 1-21.
• Pike, G.R. (1996). Limitations of Using Students’ Self-Reports of Academic Development as Proxies for Traditional Achievement Measures. Research in Higher Education, 37, 89-114.
• Pines, A.L. and West, L.H.T. (1986). Conceptual understanding and science learning: an interpretation of research within and sources-of-knowledge framework. Science Education, 70, 583-604.
• Rabovsky, M., W. Sommer and R.A. Rahman. (2012). The Time Course of Semantic Richness Effects in Visual Word Recognition. Frontiers in Human Neuroscience, 6, 1-9.
• Rahimi, M. and S. Abedi. (2015). The Role of Metacognitive Awareness of Listening Strategies in Listening Proficiency: The Case of Language Learners with Different Levels of Academic Self-Regulation. Metacognition: Fundaments, Applications, and Trends Intelligent Systems Reference Library, 76, 169-192.
• Rector, M.A., R.H. Nehm and D. Pearl. (2013). Learning the Language of Evolution: Lexical Ambiguity and Word Meaning in Student Explanations. Research in Science Education, 43, 1107-1133.
• Rubenstein, H., Garfield, L. and Millikan, J.A. (1970). Homographic entries in the internal lexicon. Journal of verbal learning and verbal behavior. 9, 487-494.
• Santos, A., S.E. Chaigneau, W.K. Simmons and L.W. Barsalou (2011). Property Generation Reflects Word Association and Situated Simulation. Language and Cognition, 3, 83-119.
• Schmeck, R.R., Ribich, F and Ramanaiah, N. (1977). Development of a Self-Report Inventory for Assessing Individual Differences in Learning Processes. Applied Psychological Measurement, 1, 413-431.
• Sharp, D. (2005). Small Latin, Even Less Greek. The Lancet, 366, 794.
• Smith, S.B., Carmichael, S.W., Pawlina, W. and Spinner, R.J. (2007). Latin and Greek in gross anatomy. Clinical Anatomy, 20, 332-337.
• Snow, C.E. (2010). Academic Language and the Challenge of Reading for Learning About Science. Science, 328, 450-452.
• Stanley, J.C. and B.S.K. Stanley. (1986). High-School Biology, Chemistry, or Physics Learned Well in Three Weeks. Journal of Research in Science Teaching, 23, 237-250.
• Sutton, C. (1992). Words, Science and Learning. Developing Science and Technology Education. Buckingham: Open University Press.
• Taft, M. (1979). Lexical access via an orthographic code: the basic orthographic syllabic structure (BOSS). Journal of Verbal Learning and Verbal Behavior, 18, 21-39.
• Taft, M. (1985). The decoding of words in the lexical access: a review of the morphographic approach. In: Besner, D., Waller, T.G. & MacKinnon, G.E. (Eds.) Reading Research: advances in theory and practice, vol. 5. (pp. 83-123), Toronto: Academic Press.
• Tyler, A. and Nagy, W. (1990). Use of derivational morphology during reading. Cognition, 36, 17-34.
• Veenman, M.V.J., B.H.A.A. Van Hout-Walters and P. Afflerbach. (2006). Metacognition and Learning: Conceptual and Methodological Considerations. Metacognition Learning, 1, 3-14.
• Wandersee, J.H. (1988). The Terminology Problem in Biology Education: A Reconnaissance. The American Biology Teacher, 50, 97-100.
• Wellington, J. and Osborne, J. (2001). Language and Literacy in Science Education. Buckingham : Open University Press.
• Wenden, A. (1987). Metacognition: an expanded view on the cognitive abilities of L2 learners. Language Learning, 37, 573-597.
• Wittrock, M.C. (1974). Learning as a generative process. Educational Psychologist, 11, 87-95.
• Yap, M.J. and D.A. Balota. (2009). Visual Word Recognition of Multisyllabic Words. Journal of Memory and Language, 60, 502-529.
• Yap, M.J., D.A. Balota, C. Tse and D. Besner. (2008). On the Additive Effects of Stimulus Quality and Word Frequency in Lexical Decision: Evidence for Opposing Interactive Influences Revealed by RT Distributional Analyses. Journal of Experimental Psychology, 34, 495-513.