Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning

Keith E. Nelson; Aran Barlieb; Kiren Khan; Elisabeth M. Vance Trup; Mikael Heimann; Tomas Tjus; Mary Rudner; Jerker Ronnberg

doi:10.30935/cedtech/6077

Keith E. Nelson ¹ ^*, Aran Barlieb ¹, Kiren Khan ¹, Elisabeth M. Vance Trup ¹, Mikael Heimann ², Tomas Tjus ³, Mary Rudner ², Jerker Ronnberg ²

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CONT ED TECHNOLOGY, Volume 3, Issue 3, pp. 184-200

https://doi.org/10.30935/cedtech/6077

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Abstract

How individual differences in information processing affect second language (L2) learning has been unclear in prior research. Adults lacking prior skill in Swedish were pretested for working memory, processing speed, and executive memory capacity. Participants then received 6 computer-based instructional sessions with pictorial animations of Swedish sentences, with a built-in experimental contrast between some lessons at high and some at low rates of presentation. The faster rate carried greater processing demands for the learners. Higher levels of Swedish performance during Instructional sessions were associated with higher working memory levels, as expected from widely-used models of working memory (e.g., Baddeley & Hitch, 1994). In contrast, results at demanding long-term retrieval on a posttest were more complex and revealed several dynamic relationships between processing speed, working memory, and Swedish language learning. Learners with low rather than high working memory showed higher L2 skills at long-term testing when instructional lessons had employed fast animations. This first-time demonstration that prior cognitive profiles strongly influence learners’ progress in second language requires refinements in existing theories. Further, the results hold certain implications for tailoring second language teaching on-line or in other technology-based instruction to learner profiles on abilities in working memory, processing speed, and executive memory

Keywords: Educational technology, Software, Designing learner-sensitive procedures, Computer-assisted learning, Second language acquisition, Dynamic systems

References

Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Science, 4, 593-596.
Baddeley, A., Gathercole, S., & Papagno, C. (1998). The phonological loop as a language learning device. Psychological Review, 105(1), 158-173.
Baddeley, A. & Hitch, G. (1994). Developments in the concept of working memory. Neuropsychology, 8(4), 485-493.
Calvin, W. (1990). The cerebral symphony. New York: Bantam.
Cradler, J. (2003). Technology's impact on teaching and learning. Learning and Leading with Technology, 30, 54-57.
Cowan, N. (2005). Working memory capacity. New York: Psychology Press.
Demetriou, A., Christou, C., Spanoudis, G., & Platsidou, M. (2002). The development of mental processing: efficiency, working memory, and thinking. Hoboken: Wiley-Blackwell.
Elman, J. L., Bates, E. A., Johnson, M. H., Karmiloff-Smith, A., Parisi, D., & Plunkett, K. (1996). Rethinking innateness: A connectionist perspective on development. Cambridge, MA: MIT Press.
Erlandson, B. E., Nelson, B. C., & Savenye, W. (2010). Collaboration modality, cognitive load, and science inquiry learning in virtual inquiry environments. Educational Technology Research & Development, 58, 693-710.
Fiddler, M. B. & Knoll, J. W. (1995). Problem-based learning in an adult liberal learning context: Learner adaptations and feedback. Continuing Higher Education Review, 59(1/2), 13–24.
Gathercole, S. & Baddeley, S. (1989). Evaluation of the role of phonological STM in the development of vocabulary in children: a longitudinal study. Journal of Memory and Language, 28, 1-14.
Gathercole, S. & Baddeley, A. (1993). Working Memory and Language. Hillsdale, NJ: Lawrence Erlbaum Associates.
Gathercole, S.E., Service, E., Hitch G.J., Adams, A. & Martin, A.J. (1999) Phonological short term memory and vocabulary development: further evidence on the nature of the relationship. Applied Cognitive Psychology, 13, 65-77.
Gathercole, S. E., Willis, C., Emslie, H., & Baddeley, A.D. (1992). Phonological memory and vocabulary development during the early school years: A longitudinal study. Developmental Psychology, 28, 887–898.
Gillum, H., Camarata, S., Nelson, K. E., & Camarata, M. N. (2003). A comparison of naturalistic and analog treatment effects in children with expressive language disorder and poor preintervention imitation skills. Journal of Positive Behavioral Interventions, 5, 171-178.
Gupta, P. & MacWhinney, B. (1997). Vocabulary acquisition and short-term memory: Computational and neural bases. Brain and Language, 59, 267-333.
Heimann, M., Lundalv, M., Tjus, T., & Nelson, K. E. Omega-is: Omega interactive sentences software. Gothenburg, Sweden: Topic Dos Hb, and Warriors Mark, PA, United States: Super Impact Images Inc.
Hung, W. (2011). Theory to reality: a few issues in implementing problem-based learning. Educational Technology Research & Development, 59, 529-552.
Hung, W. (2006). The 3C3R model: A conceptual framework for designing problems in PBL. Interdisciplinary Journal of Problem-based Learning, 1, 55–77.
Hung, W. (2009). The 9-step process for designing PBL problems: Application of the 3C3R model. Educational Research Review, 4(2), 118–141.
Jonassen, D. H. & Hung, W. (2008). All problems are not equal: Implications for PBL. Interdisciplinary Journal of Problem-Based Learning, 2(2), 6–28.
Just, M. & Carpenter, P. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122-149.
LaGrange, J. B., Artigue, M., Laborde, C., & Trouche, L. (2001). A meta-study on IC technologies in education: Towards a multidimensional framework to tackle their integration. Paper presented at the Proceedings of the 25th Conference of the International Group for the Psychology of Mathematics Education. ERIC document: ED 466 950.
Lonigan, C. J., Wagner, R. K., Torgeson, J. K., & Rashotte, C. A. (2002). Preschool comprehensive test of phonological processing. Florida State University.
MacWhinney, B. (2008). A unified model. Handbook of cognitive linguistics and second language acquisition (pp. 341-371). New York: Routledge.
Miyake, A. & Shah, P. (Eds.). (1999). Models of working memory: Mechanisms of active maintenance and executive control. Cambridge: Cambridge University Press.
Nelson, K. E. (1991). On differentiated language-learning models and differentiated interventions. In N. A. Krasnegor, D. M. Rumbaugh, R. L. Schiefusbusch, & M. Studdert-Kennedy (Eds.), Biological and behavioral determinants of language development. Hillsdale, NJ: Erlbaum.
Nelson, K. E. (2000). Methods for stimulating and measuring lexical and syntactic advances: Why Fiffins and lobsters can tag along with other recast friends. In L. Menn & N. B. Ratner (Eds.), Methods for studying language production. Hillsdale, NJ. Erlbaum.
Nelson, K. (2006). A dynamic tricky mix theoretical perspective on educational interventions to support the acquisition of L1 and L2 spoken languages, sign languages, text, and art. Studies in Language Sciences, 5, 91-102.
Nelson, K. E., Welsh, J., Camarata, S., Heimann, & Tjus, T. (2001). A rare event transactional dynamic model of tricky mix conditions contributing to language acquisition and varied communicative delays. In K. E. Nelson, A. Aksu-Koc, & C. E. Johnson (Eds.), Children's language, Vol. 11. Hillsdale, NJ: Erlbaum.
Nelson, K. E., Craven, P. L., Xuan, Y., & Arkenberg, M. E. (2004). Acquiring art, spoken language, sign language, text, and other symbolic systems: Developmental and evolutionary observations from a Dynamic Tricky Mix theoretical perspective. In J. M. Lucariello, J. A. Harris, R. Fivush, & P. J. Bauer (Eds.), The development of the mediated mind. Sociocultural context and cognitive development (pp. 175-222). Mahwah, NJ: Lawrence Erlbaum Associates.
Nelson, K. & Arkenberg, M. (2008). Language and reading development reflect dynamic mixes of learning conditions. Brain, behavior, and learning in language and reading disorders (pp. 315-348). New York: Guilford Press.
Newport, E.L. (1990). Maturational constraints on language learning. Cognitive Science, 14, 11-28.
Peltzer-Karpf, A. & Zangl, R. (2001). Figure-ground segregation in visual and linguistic development: A Dynamic Systems Account. In K. E. Nelson, A. Aksu-Koc, & C. E. Johnson (Eds.), Children's language, Vol. 11. Hillsdale, NJ: Erlbaum.
Repovs. G. & Baddeley, A. (2006). The multi-component model of working memory: Explorations in experimental cognitive psychology. Neuroscience, 139, 5-21.
Roberts, R. & Pennington, B. (1996). An interactive framework for examining prefrontal cognitive processes. Developmental Neuropsychology, 12(1), 105-126.
Ronnberg, J., Rudner, M., Foo, C., & Lunner, T. (2008). Cognition counts: A working memory system for ease of language understanding (ELU). International Journal of Audiology, 47, 171-2177.
Shallice, T. (2004). The fractionation of supervisory control. In M. Gazzaniga (Ed.), The cognitive neurosciences (3rd ed.) (pp. 1265-1277). Cambridge, MA: MIT Press.
Thelen, E. & Smith, L. (1996). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT Press.
Turner, M. L. & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28, 127-154.

Citation

Nelson, K. E., Barlieb, A., Khan, K., Trup, E. M. V., Heimann, M., Tjus, T., Rudner, M., & Ronnberg, J. (2012). Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning. Contemporary Educational Technology, 3(3), 184-200. https://doi.org/10.30935/cedtech/6077

Nelson, K. E., Barlieb, A., Khan, K., Trup, E. M. V., Heimann, M., Tjus, T., . . . Ronnberg, J. (2012). Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning. Contemporary Educational Technology, 3(3), pp. 184-200. https://doi.org/10.30935/cedtech/6077

Nelson KE, Barlieb A, Khan K, et al. Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning. CONT ED TECHNOLOGY. 2012;3(3), 184-200. https://doi.org/10.30935/cedtech/6077

Nelson, Keith E., Aran Barlieb, Kiren Khan, Elisabeth M. Vance Trup, Mikael Heimann, Tomas Tjus, Mary Rudner, and Jerker Ronnberg. "Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning". Contemporary Educational Technology 2012 3 no. 3 (2012): 184-200. https://doi.org/10.30935/cedtech/6077

Nelson, Keith E. et al. "Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning". Contemporary Educational Technology, vol. 3, no. 3, 2012, pp. 184-200. https://doi.org/10.30935/cedtech/6077

Nelson KE, Barlieb A, Khan K, Trup EMV, Heimann M, Tjus T, et al. Working Memory, Processing Speed, and Executive Memory Contributions to Computer-Assisted Second Language Learning. CONT ED TECHNOLOGY. 2012;3(3):184-200. https://doi.org/10.30935/cedtech/6077