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Educational Psychology Review

, Volume 29, Issue 2, pp 235–268 | Cite as

Toward a Dynamic, Multidimensional Research Framework for Strategic Processing

  • Daniel L. DinsmoreEmail author
Review Article

Abstract

While the empirical literature on strategic processing is vast, understanding how and why certain strategies work for certain learners is far from clear. The purpose of this review is to systematically examine the theoretical and empirical literature on strategic process to parse out current conceptual and methodological progress to inform new conceptual and methodological approaches to investigating strategic processing. From a PsycINFO search from 2011 to 2016, a pool of 134 studies was tabled with regard to key conceptual and methodological characteristics along with salient findings. These conceptual and methodological findings were then synthesized to examine how development, three aspects of strategic processing, and personal and environmental factors explained the relation between strategic processing and performance in academic domains. Three major findings emerged: less is known empirically about the developmental nature of strategic processing; quality and conditional use explain performance more consistently than simply frequency of strategy use; and, numerous person and environmental factors shape the degree to which certain strategies are effective for certain learners. A framework for future research based on these three findings is presented.

Keywords

Strategies Strategic processing Dynamic systems Relational tradition 

Notes

Acknowledgments

Thanks to Misa Watanabe for her help in the literature search as well as organizing and downloading articles for the literature review table.

Compliance with Ethical Standards

Conflict of Interest

The author declares that he has no conflict of interest.

References

  1. Aghaie, R., & Zhang, L. J. (2012). Effects of explicit instruction in cognitive and metacognitive reading strategies on Iranian EFL students’ reading performance and strategy transfer. Instructional Science, 40, 1063–1081.CrossRefGoogle Scholar
  2. Alexander, P. A. (1997). Mapping the multidimensional nature of domain learning: The interplay of cognitive, motivational, and strategic forces. In M. L. Maehr & P. R. Pintrich (Eds.), Advances in motivation and achievement (Vol. 10, pp. 213–250). Greenwich: JAI.Google Scholar
  3. Alexander, P. A. (2003). The development of expertise: the journey from acclimation to proficiency. Educational Researcher, 32, 10–14.CrossRefGoogle Scholar
  4. Alexander, P. A. (2004). A model of domain learning: Reinterpreting expertise as a multidimensional, multistage process. In D. Y. Dai & R. J. Sternberg (Eds.), Motivation, emotion, and cognition: integrative perspectives on intellectual functioning and development (pp. 273–298). Mahwah: Erlbaum.Google Scholar
  5. Alexander, P. A., Jetton, T. L., & Kulikowich, J. M. (1995). Interrelationship of knowledge, interest, and recall: assessing a model of domain learning. Journal of Educational Psychology, 87, 559–575.CrossRefGoogle Scholar
  6. Alexander, P. A., Graham, S., & Harris, K. R. (1998). A perspective on strategy research: progress and prospects. Educational Psychology Review, 10, 129–154.CrossRefGoogle Scholar
  7. Alexander, P. A., Sperl, C. T., Buehl, M. M., Fives, H., & Chiu, S. (2004). Modeling domain learning: profiles from the field of special education. Journal of Educational Psychology, 96, 545–557.CrossRefGoogle Scholar
  8. Alexander, P. A., Grossnickle, E. M., Dumas, D., & Hattan, C. (2017). A retrospective and prospective examination of cognitive strategies and academic development: Where have we come in twenty-five years? In A. O’Donnell (Ed.), Handbook of educational psychology. Oxford University Press.Google Scholar
  9. Anglim, J., & Wynton, S. K. (2015). Hierarchical Bayesian models of subtask learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 957–974.Google Scholar
  10. Anmarkrud, Ø., Bråten, I., & Strømsø, H. I. (2014). Multiple-documents literacy: strategic processing, source awareness, and argumentation when reading multiple conflicting documents. Learning and Individual Differences, 30, 64–76.CrossRefGoogle Scholar
  11. Anmarkrud, Ø., McCrudden, M. T., Bråten, I., & Strømsø, H. I. (2013). Task-oriented reading of multiple documents: online comprehension processes and offline products. Instructional Science, 41, 873–894.CrossRefGoogle Scholar
  12. Arya, P., & Feathers, K. M. (2012). Reconsidering children’s readings: insights into the reading process. Reading Psychology, 33, 301–322.CrossRefGoogle Scholar
  13. Asaro-Saddler, K., & Bak, N. (2012). Teaching children with high-functioning autism spectrum disorders to write persuasive essays. Topics in Language Disorders, 32, 361–378.CrossRefGoogle Scholar
  14. Askeland, M. (2012). Sound-based strategy training in multiplication. European Journal of Special Needs Education, 27, 201–217.CrossRefGoogle Scholar
  15. Askell-Williams, H., Lawson, M. J., & Skrzypiec, G. (2012). Scaffolding cognitive and metacognitive strategy instruction in regular class lessons. Instructional Science, 40, 413–443.CrossRefGoogle Scholar
  16. Baas, D., Castelijns, J., Vermeulen, M., Martens, R., & Segers, M. (2015). The relation between assessment for learning and elementary students’ cognitive and metacognitive strategy use. British Journal of Educational Psychology, 85, 33–46.CrossRefGoogle Scholar
  17. Barkaoui, K., Brooks, L., Swain, M., & Lapkin, S. (2012). Test-takers’ strategic behaviors in independent and integrated speaking tasks. Applied Linguistics, 1–22.Google Scholar
  18. Baroody, A. J., Purpura, D. J., Eiland, M. D., & Reid, E. E. (2014). Fostering first graders’ fluency with basic subtraction and larger addition combinations via computer-assisted instruction. Cognition and Instruction, 32, 159–197.CrossRefGoogle Scholar
  19. Bartels, J. M., Magun-Jackson, S., & Ryan, J. J. (2011). Achievement goals, volitional regulation and help-seeking among college students: a multiple goal analysis. Individual Differences Research, 9, 41–51.Google Scholar
  20. Bebko, J. M., Rhee, T., McMorris, C. A., & Ncube, B. L. (2015). Spontaneous strategy use in children with autism spectrum disorder: the roles of metamemory and language skills. Frontiers in Psychology, 6, 1–10.CrossRefGoogle Scholar
  21. Belet, S. D., & Guven, M. (2011). Meta-cognitive strategy usage and epistemological beliefs of primary school teacher trainees. Educational Sciences: Theory and Practice, 11, 51–57.Google Scholar
  22. Berger, J. L., & Karabenick, S. A. (2011). Motivation and students’ use of learning strategies: evidence of unidirectional effects in mathematics classrooms. Learning and Instruction, 21, 416–428.CrossRefGoogle Scholar
  23. Bernacki, M. L., Byrnes, J. P., & Cromley, J. G. (2012). The effects of achievement goals and self-regulated learning behaviors on reading comprehension in technology-enhanced learning environments. Contemporary Educational Psychology, 37, 148–161.CrossRefGoogle Scholar
  24. Biggs, J. B. (1978). Individual and group differences in study processes. British Journal of Educational Psychology, 48, 266–279.CrossRefGoogle Scholar
  25. Bonner, S. M. (2013). Mathematics strategy use in solving test items in varied formats. The Journal of Experimental Education, 81, 409–428.CrossRefGoogle Scholar
  26. Cantrell, S. C., Almasi, J. F., Rintamaa, M., Carter, J. C., Pennington, J., & Buckman, D. M. (2014). The impact of supplemental instruction on low-achieving adolescents’ reading engagement. The Journal of Educational Research, 107, 36–58.CrossRefGoogle Scholar
  27. Carr, M., & Alexeev, N. (2011). Fluency, accuracy, and gender predict developmental trajectories of arithmetic strategies. Journal of Educational Psychology, 103, 617–631.CrossRefGoogle Scholar
  28. Carr, M., Taasoobshirazi, G., Stroud, R., & Royer, J. M. (2011). Combined fluency and cognitive strategies instruction improves mathematics achievement in early elementary school. Contemporary Educational Psychology, 36, 323–333.CrossRefGoogle Scholar
  29. Chatzistamatiou, M., Dermitzaki, I., Efklides, A., & Leondari, A. (2015). Motivational and affective determinants of self-regulatory strategy use in elementary school mathematics. Educational Psychology, 35, 835–850.CrossRefGoogle Scholar
  30. Chen, C. H., & Wu, I. C. (2012). The interplay between cognitive and motivational variables in a supportive online learning system for secondary physical education. Computers & Education, 58, 542–550.CrossRefGoogle Scholar
  31. Chen, C. Y., & Pedersen, S. (2012). Learners’ internal management of cognitive processing in online learning. Innovations in Education and Teaching International, 49, 363–373.CrossRefGoogle Scholar
  32. Chen, L., Zhang, R., & Liu, C. (2014). Listening strategy use and influential factors in web-based computer assisted language learning. Journal of Computer Assisted Learning, 30, 207–219.CrossRefGoogle Scholar
  33. Cho, B. Y. (2013). Adolescents’ constructively responsive reading strategy use in a critical Internet reading task. Reading Research Quarterly, 48, 329–332.CrossRefGoogle Scholar
  34. Cho, B. Y. (2014). Competent adolescent readers’ use of internet reading strategies: a think-aloud study. Cognition and Instruction, 32, 253–289.CrossRefGoogle Scholar
  35. Cho, Y., Weinstein, C. E., & Wicker, F. (2011). Perceived competence and autonomy as moderators of the effects of achievement goal orientations. Educational Psychology, 31, 393–411.CrossRefGoogle Scholar
  36. Chou, M. H. (2013). Strategy use for reading English for general and specific academic purposes in testing and nontesting contexts. Reading Research Quarterly, 48, 175–197.CrossRefGoogle Scholar
  37. Cobb, J. B. (2012). “It’s me. I’m fixin’to know the hard words”: children’s perceptions of “good readers” as portrayed in their representational drawings. Journal of Research in Childhood Education, 26, 221–236.CrossRefGoogle Scholar
  38. Cooper, H. (2010). Research synthesis and meta-analysis: a step-by-step approach (4th ed.). Thousand Oaks: Sage.Google Scholar
  39. Conradi, K., Jang, B. G., & McKenna, M. C. (2014). Motivation terminology in reading research: a conceptual review. Educational Psychology Review, 26, 127–164.CrossRefGoogle Scholar
  40. Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: a framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11, 671–684.CrossRefGoogle Scholar
  41. Cromley, J., & Azevedo, R. (2011). Measuring strategy use in context with multiple-choice items. Metacognition and Learning, 6, 155–177.CrossRefGoogle Scholar
  42. Cunningham, A. J., & Carroll, J. M. (2015). Early predictors of phonological and morphological awareness and the link with reading: evidence from children with different patterns of early deficit. Applied PsychoLinguistics, 36, 509–531.CrossRefGoogle Scholar
  43. De Backer, L., Van Keer, H., & Valcke, M. (2012). Exploring the potential impact of reciprocal peer tutoring on higher education students’ metacognitive knowledge and regulation. Instructional Science, 40, 559–588.CrossRefGoogle Scholar
  44. de Bilde, J., Vansteenkiste, M., & Lens, W. (2011). Understanding the association between future time perspective and self-regulated learning through the lens of self-determination theory. Learning and Instruction, 21, 332–344.CrossRefGoogle Scholar
  45. Denton, C. A., Wolters, C. A., York, M. J., Swanson, E., Kulesz, P. A., & Francis, D. J. (2015). Adolescents’ use of reading comprehension strategies: differences related to reading proficiency, grade level, and gender. Learning and Individual Differences, 37, 81–95.CrossRefGoogle Scholar
  46. Dinsmore, D. L. (2014). Perspectives on learning in the 21st century: Examining changing constructs, methods, and contexts. In L. Fryer (Ed.), 20th Century Models of Student Learning at a 21st Century Crossroad. Symposium presented at the biennial meeting of the European Association for Research on Learning and Instruction for SIG 4 Higher Education, Leuven.Google Scholar
  47. Dinsmore, D. L., & Alexander, P. A. (2012). A critical discussion of deep and surface processing: what it means, how it is measured, the role of context, and model specification. Educational Psychology Review, 24, 499–567.CrossRefGoogle Scholar
  48. Dinsmore, D. L., & Alexander, P. A. (2016). A multidimensional investigation of deep-level and surface-level processing. Journal of Experimental Education, 84, 213–244.CrossRefGoogle Scholar
  49. Dinsmore, D. L., Alexander, P. A., & Loughlin, S. M. (2008). Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review, 20, 391–409.CrossRefGoogle Scholar
  50. Dinsmore, D. L., Grossnickle, E. M., & Dumas, D. (2016). Learning to study strategically. In R. E. Mayer & P. A. Alexander (Eds.), Handbook of research on learning and teaching: second edition. New York: Routledge.Google Scholar
  51. Donne, V., & Rugg, N. (2015). Online reading practices of students who are deaf/hard of hearing. Deafness & Education International, 17, 144–154.CrossRefGoogle Scholar
  52. Donovan, J. L., & Marshall, C. R. (2015). Comparing the verbal self-reports of spelling strategies used by children with and without dyslexia. International Journal of Disability, Development and Education, 63, 1–18.Google Scholar
  53. Dornisch, M., Sperling, R. A., & Zeruth, J. A. (2011). The effects of levels of elaboration on learners’ strategic processing of text. Instructional Science, 39, 1–26.CrossRefGoogle Scholar
  54. Dressler, C., Carlo, M. S., Snow, C. E., August, D., & White, C. E. (2011). Spanish-speaking students’ use of cognate knowledge to infer the meaning of English words. Bilingualism: Language and Cognition, 14, 243–255.CrossRefGoogle Scholar
  55. Fabriz, S., Dignath-van Ewijk, C., Poarch, G., & Büttner, G. (2014). Fostering self-monitoring of university students by means of a standardized learning journal—a longitudinal study with process analyses. European Journal of Psychology of Education, 29, 239–255.CrossRefGoogle Scholar
  56. Farrington-Flint, L. (2015). Uncovering strategy profiles in young children’s reading & spelling. Learning and Individual Differences, 42, 64–69.CrossRefGoogle Scholar
  57. Fazio, L. K., DeWolf, M., & Siegler, R. S. (2016). Strategy use and strategy choice in fraction magnitude comparison. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42, 1–16.Google Scholar
  58. Flavell, J. H. (1979). Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911.CrossRefGoogle Scholar
  59. Freeman-Green, S. M., O’Brien, C., Wood, C. L., & Hitt, S. B. (2015). Effects of the SOLVE strategy on the mathematical problem solving skills of secondary students with learning disabilities. Learning Disabilities Research & Practice, 30, 76–90.CrossRefGoogle Scholar
  60. Ghavamnia, M., Ketabi, S., & Tavakoli, M. (2013). L2 reading strategies used by Iranian EFL learners: a think-aloud study. Reading Psychology, 34, 355–378.CrossRefGoogle Scholar
  61. Gijbels, D., Donche, V., Richardson, J. T., & Vermunt, J. D. (2013). Learning patterns in higher education: dimensions and research perspectives. New York: Routledge.Google Scholar
  62. Grammer, J. K., Purtell, K. M., Coffman, J. L., & Ornstein, P. A. (2011). Relations between children’s metamemory and strategic performance: time-varying covariates in early elementary school. Journal of Experimental Child Psychology, 108, 139–155.CrossRefGoogle Scholar
  63. Grammer, J., Coffman, J. L., & Ornstein, P. (2013). The effect of teachers’ memory-relevant language on children’s strategy use and knowledge. Child Development, 84, 1989–2002.CrossRefGoogle Scholar
  64. Greene, J. A., & Azevedo, R. (2010). The measurement of learners’ self-regulated cognitive and metacognitive processes while using computer-based learning environments. Educational Psychologist, 45, 203–209.CrossRefGoogle Scholar
  65. Greene, J. A., Muis, K. R., & Pieschl, S. (2010). The role of epistemic beliefs in students’ self-regulated learning with computer-based learning environments: conceptual and methodological issues. Educational Psychologist, 45, 245–257.CrossRefGoogle Scholar
  66. Greene, J. A., Bolick, C. M., Jackson, W. P., Caprino, A. M., Oswald, C., & McVea, M. (2015). Domain-specificity of self-regulated learning processing in science and history. Contemporary Educational Psychology, 42, 111–128.CrossRefGoogle Scholar
  67. Grenfell, M., & Harris, V. (2015). Memorisation strategies and the adolescent learner of Mandarin Chinese as a foreign language. Linguistics and Education, 31, 1–13.CrossRefGoogle Scholar
  68. Griffiths, G. G., Sohlberg, M. M., Kirk, C., Fickas, S., & Biancarosa, G. (2016). Evaluation of use of reading comprehension strategies to improve reading comprehension of adult college students with acquired brain injury. Neuropsychological Rehabilitation, 26, 161–190.CrossRefGoogle Scholar
  69. Hagen, Å. M., Braasch, J. L., & Bråten, I. (2014). Relationships between spontaneous note-taking, self-reported strategies and comprehension when reading multiple texts in different task conditions. Journal of Research in Reading, 37, 141–S157.CrossRefGoogle Scholar
  70. Hartwig, M. K., & Dunlosky, J. (2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19, 126–134.CrossRefGoogle Scholar
  71. He, T. H., Chang, S. M., & Chen, S. H. E. (2011). Multiple goals, writing strategies, and written outcomes for college students learning English as a second language. Perceptual and Motor Skills, 112, 401–416.CrossRefGoogle Scholar
  72. Helman, A. L., Calhoon, M. B., & Kern, L. (2015). Improving science vocabulary of high school English language learners with reading disabilities. Learning Disability Quarterly, 38, 40–52.CrossRefGoogle Scholar
  73. Hertzog, C., Price, J., & Dunlosky, J. (2012). Age differences in the effects of experimenter-instructed versus self-generated strategy use. Experimental Aging Research, 38, 42–62.CrossRefGoogle Scholar
  74. Hickendorff, M. (2013). The effects of presenting multidigit mathematics problems in a realistic context on sixth graders’ problem solving. Cognition and Instruction, 31, 314–344.CrossRefGoogle Scholar
  75. Hong-Nam, K., & Page, L. (2014). Investigating metacognitive awareness and reading strategy use of EFL Korean university students. Reading Psychology, 35, 195–220.CrossRefGoogle Scholar
  76. Hong-Nam, K., Leavell, A. G., & Maher, S. (2014). The relationships among reported strategy use, metacognitive awareness, and reading achievement of high school students. Reading Psychology, 35, 762–790.CrossRefGoogle Scholar
  77. Hu, H., & Driscoll, M. P. (2013). Self-regulation in e-learning environments: a remedy for community college? Educational Technology & Society, 16, 171–184.Google Scholar
  78. Hwang, J., & Yun, Z. S. (2015). Mechanism of psychological distress-driven smoking addiction behavior. Journal of Business Research, 68, 2189–2197.CrossRefGoogle Scholar
  79. Jairam, D., Kiewra, K. A., Kauffman, D. F., & Zhao, R. (2012). How to study a matrix. Contemporary Educational Psychology, 37, 128–135.CrossRefGoogle Scholar
  80. James, W. (1899). Talks to teachers on psychology. New York: Henry Holt and Company.Google Scholar
  81. Johnson, M. L., Taasoobshirazi, G., Kestler, J. L., & Cordova, J. R. (2015). Models and messengers of resilience: a theoretical model of college students’ resilience, regulatory strategy use, and academic achievement. Educational Psychology, 35, 869–885.CrossRefGoogle Scholar
  82. Kang, Y. S., & Pyun, D. O. (2013). Mediation strategies in L2 writing processes: a case study of two Korean language learners. Language, Culture and Curriculum, 26, 52–67.CrossRefGoogle Scholar
  83. Kaplan, Katz, & Flum. (2012). Motivational theory in educational practice: Knowledge claims, challenges, and future directions. In K. R. Harris, S. Graham, T. Urdan, S. Graham, J. M. Royer, & M. Zeidner (Eds.), APA educational psychology handbook (volume II: individual differences and cultural and contextual factors; pp. 165–194). Washington D.C.: American Psychological Association.Google Scholar
  84. Karimi, M. N. (2015). EFL learners’ multiple documents literacy: effects of a strategy-directed intervention program. The Modern Language Journal, 99, 40–56.CrossRefGoogle Scholar
  85. Kim, C., Park, S. W., & Cozart, J. (2014). Affective and motivational factors of learning in online mathematics courses. British Journal of Educational Technology, 45, 171–185.CrossRefGoogle Scholar
  86. King, R. B., & Areepattamannil, S. (2014). What students feel in school influences the strategies they use for learning: academic emotions and cognitive/meta-cognitive strategies. Journal of Pacific Rim Psychology, 8, 18–27.CrossRefGoogle Scholar
  87. Kıran, D., & Sungur, S. (2012). Middle school students’ science self-efficacy and its sources: examination of gender difference. Journal of Science Education and Technology, 21, 619–630.CrossRefGoogle Scholar
  88. Kırmızı, F. S. (2011). The relationship between reading comprehension strategies and reading attitudes. Education, 39, 289–303.Google Scholar
  89. Kragler, S., Martin, L., & Schreier, V. (2015). Investigating young children’s use of reading strategies: a longitudinal study. Reading Psychology, 36, 445–472.CrossRefGoogle Scholar
  90. Künsting, J., Wirth, J., & Paas, F. (2011). The goal specificity effect on strategy use and instructional efficiency during computer-based scientific discovery learning. Computers & Education, 56, 668–679.CrossRefGoogle Scholar
  91. Künsting, J., Kempf, J., & Wirth, J. (2013). Enhancing scientific discovery learning through metacognitive support. Contemporary Educational Psychology, 38, 349–360.CrossRefGoogle Scholar
  92. Lau, K. L. (2011). Collaborating with front-line teachers to incorporate self-regulated learning in Chinese language classes. Educational Research and Evaluation, 17, 47–66.CrossRefGoogle Scholar
  93. Lau, K. L. (2012). Instructional practices and self-regulated learning in Chinese language classes. Educational Psychology, 32, 427–450.CrossRefGoogle Scholar
  94. Lau, K. L., & Chen, X. B. (2013). Perception of reading instruction and self-regulated learning: a comparison between Chinese students in Hong Kong and Beijing. Instructional Science, 41, 1083–1101.CrossRefGoogle Scholar
  95. Lee, P. A., & Schmitt, M. C. (2014). Teacher language scaffolds the development of independent strategic reading activities and metacognitive awareness in emergent readers. Reading Psychology, 35, 32–57.CrossRefGoogle Scholar
  96. Legare, C. H., Mills, C. M., Souza, A. L., Plummer, L. E., & Yasskin, R. (2013). The use of questions as problem-solving strategies during early childhood. Journal of Experimental Child Psychology, 114, 63–76.CrossRefGoogle Scholar
  97. Leopold, C., Sumfleth, E., & Leutner, D. (2013). Learning with summaries: effects of representation mode and type of learning activity on comprehension and transfer. Learning and Instruction, 27, 40–49.CrossRefGoogle Scholar
  98. Lewandowski, L., Gathje, R. A., Lovett, B. J., & Gordon, M. (2013). Test-taking skills in college students with and without ADHD. Journal of Psychoeducational Assessment, 31, 41–52.CrossRefGoogle Scholar
  99. Liben, L. S., Kastens, K. A., & Christensen, A. E. (2011). Spatial foundations of science education: the illustrative case of instruction on introductory geological concepts. Cognition and Instruction, 29, 45–87.CrossRefGoogle Scholar
  100. Lindberg, S., Lonnemann, J., Linkersdörfer, J., Biermeyer, E., Mähler, C., Hasselhorn, M., & Lehmann, M. (2011). Early strategies of elementary school children’s single word reading. Journal of Neurolinguistics, 24, 556–570.CrossRefGoogle Scholar
  101. Liu, S. H. J., Lan, Y. J., & Ho, C. Y. Y. (2014). Exploring the relationship between self-regulated vocabulary learning and web-based collaboration. Educational Technology & Society, 17, 404–419.Google Scholar
  102. Loughlin, S. M., & Alexander, P. A. (2012). Explicating and exemplifying empiricist and cognitivist paradigms in the study of human learning. In L. L’Abate (Ed.), Paradigms in theory construction (pp. 273–296). New York: Springer.CrossRefGoogle Scholar
  103. Lust, G., Elen, J., & Clarebout, G. (2013). Students’ tool-use within a web enhanced course: explanatory mechanisms of students’ tool-use pattern. Computers in Human Behavior, 29, 2013–2021.CrossRefGoogle Scholar
  104. Malmberg, J., Järvenoja, H., & Järvelä, S. (2013). Patterns in elementary school students’ strategic actions in varying learning situations. Instructional Science, 41, 933–954.CrossRefGoogle Scholar
  105. Malmberg, J., Järvelä, S., & Kirschner, P. A. (2014). Elementary school students’ strategic learning: does task-type matter? Metacognition and Learning, 9, 113–136.CrossRefGoogle Scholar
  106. Marton, F., & Säljö, R. (1976). On qualitative differences in learning: I—outcome and process*. British Journal of Educational Psychology, 46, 4–11.CrossRefGoogle Scholar
  107. Mastropieri, M. A., Scruggs, T. E., Irby Cerar, N., Guckert, M., Thompson, C., Bronaugh, D. A., et al. (2015). Strategic persuasive writing instruction for students with emotional and behavioral disabilities. Exceptionality, 23, 147–169.CrossRefGoogle Scholar
  108. McGeown, S. P., Medford, E., & Moxon, G. (2013). Individual differences in children’s reading and spelling strategies and the skills supporting strategy use. Learning and Individual Differences, 28, 75–81.CrossRefGoogle Scholar
  109. Merchie, E., & Van Keer, H. (2014). Using on-line and off-line measures to explore fifth and sixth graders’ text-learning strategies and schematizing skills. Learning and Individual Differences, 32, 193–203.CrossRefGoogle Scholar
  110. Meteyard, L., Bruce, C., Edmundson, A., & Oakhill, J. (2015). Profiling text comprehension impairments in aphasia. Aphasiology, 29, 1–28.CrossRefGoogle Scholar
  111. Mirzaei, A., Rahimi Domakani, M., & Heidari, N. (2014). Exploring the relationship between reading strategy use and multiple intelligences among successful L2 readers. Educational Psychology, 34, 208–230.CrossRefGoogle Scholar
  112. Mok, M. M. C., Kennedy, K. J., & Moore, P. J. (2011). Academic attribution of secondary students: gender, year level and achievement level. Educational Psychology, 31, 87–104.CrossRefGoogle Scholar
  113. Molenaar, P. C. M., Lerner, R. M., & Newell, K. M. (2014). Developmental systems theory and methodology: A view of the issues. In P. C. M. Molenaar, R. M. Lerner, & K. M. Newell (Eds.), Handbook of developmental systems theory & methodology (pp. 3–18). New York: Guilford.Google Scholar
  114. Muis, K. R., & Duffy, M. C. (2013). Epistemic climate and epistemic change: instruction designed to change students’ beliefs and learning strategies and improve achievement. Journal of Educational Psychology, 105, 213–225.CrossRefGoogle Scholar
  115. Muis, K. R., & Franco, G. M. (2009). Epistemic beliefs: setting the standards for self-regulated learning. Contemporary Educational Psychology, 34, 306–318.CrossRefGoogle Scholar
  116. Muis, K. R., Ranellucci, J., Franco, G. M., & Crippen, K. J. (2013). The interactive effects of personal achievement goals and performance feedback in an undergraduate science class. The Journal of Experimental Education, 81, 556–578.CrossRefGoogle Scholar
  117. Murphy, P. K., & Alexander, P. A. (2000). A motivated exploration of motivation terminology. Contemporary Educational Psychology, 25, 3–53.CrossRefGoogle Scholar
  118. Nida, R. E. (2015). Effects of motivation on young children’s object recall and strategy use. The Journal of Genetic Psychology, 176, 194–209.CrossRefGoogle Scholar
  119. Nielsen, S. G. (2011). Epistemic beliefs and self-regulated learning in music students. Psychology of Music, 1–16.Google Scholar
  120. Noble, D. (2011). Neo-Darwinism, the modern synthesis and selfish genes: are they of use in physiology? The Journal of Physiology, 589, 1007–1015.CrossRefGoogle Scholar
  121. Nolen, S. B., & Haladyna, T. M. (1990). Personal and environmental influences on students’ beliefs about effective study strategies. Contemporary Educational Psychology, 15, 116–130.CrossRefGoogle Scholar
  122. Overton, W. F. (2014). Relational developmental systems and developmental science: A focus on methodology. In P. C. M. Molenaar, R. M. Lerner, & K. M. Newell (Eds.), Handbook of developmental systems theory & methodology (pp. 19–65). New York: Guilford.Google Scholar
  123. Park, H. R., & Kim, D. (2011). Reading-strategy use by English as a second language learners in online reading tasks. Computers & Education, 57, 2156–2166.CrossRefGoogle Scholar
  124. Park, S., & Kim, C. (2014). Virtual tutee system: a potential tool for enhancing academic reading engagement. Educational Technology Research and Development, 62, 71–97.CrossRefGoogle Scholar
  125. Peklaj, C., & Pečjak, S. (2011). Emotions, motivation and self-regulation in boys’ and girls’ learning mathematics. Horizons of Psychology, 20, 33–58.Google Scholar
  126. Peters, S., Koolschijn, P. C. M., Crone, E. A., Van Duijvenvoorde, A. C., & Raijmakers, M. E. (2014). Strategies influence neural activity for feedback learning across child and adolescent development. Neuropsychologia, 62, 365–374.CrossRefGoogle Scholar
  127. Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory Into Practice, 41, 219–225.CrossRefGoogle Scholar
  128. Pintrich, P. R., Smith, D. A., García, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53, 801–813.CrossRefGoogle Scholar
  129. Pintrich, P. R., Anderman, E. M., & Klobucar, C. (1994). Intraindividual differences in motivation and cognition in students with and without learning disabilities. Journal of Learning Disabilities, 27, 360–370.CrossRefGoogle Scholar
  130. Puvanendran, K., Dowker, A., & Demeyere, N. (2015). Compensating arithmetic ability with derived fact strategies in Broca’s aphasia: a case report. Neurocase, 1–10.Google Scholar
  131. Rabinowitz, M., & McAuley, R. (2014). The effects of ease of processing on the use and perception of strategies. Journal of Cognitive Psychology, 26, 919–927.CrossRefGoogle Scholar
  132. Reed, H. C., Stevenson, C., Broens-Paffen, M., Kirschner, P. A., & Jolles, J. (2015). Third graders’ verbal reports of multiplication strategy use: How valid are they? Learning and Individual Differences, 37, 107–117.CrossRefGoogle Scholar
  133. Resing, W., & Elliott, J. G. (2011). Dynamic testing with tangible electronics: measuring children’s change in strategy use with a series completion task. British Journal of Educational Psychology, 81, 579–605.CrossRefGoogle Scholar
  134. Richardson, J. T. (2015). Approaches to learning or levels of processing: What did Marton and Säljö (1976a) really say? The legacy of the work of the Göteborg group in the 1970s. Interchange, 46, 239–269.CrossRefGoogle Scholar
  135. Rieser, S., Fauth, B. C., Decristan, J., Klieme, E., & Büttner, G. (2013). The connection between primary school students’ self-regulation in learning and perceived teaching quality. Journal of Cognitive Education and Psychology, 12, 138–156.CrossRefGoogle Scholar
  136. Ruffing, S., Hahn, E., Spinath, F. M., Brünken, R., & Karbach, J. (2015a). Predicting students’ learning strategies: the contribution of chronotype over personality. Personality and Individual Differences, 85, 199–204.CrossRefGoogle Scholar
  137. Ruffing, S., Wach, F. S., Spinath, F. M., Brünken, R., & Karbach, J. (2015b). Learning strategies and general cognitive ability as predictors of gender-specific academic achievement. Frontiers in Psychology, 6, 1–12.CrossRefGoogle Scholar
  138. Schwinger, M., Steinmayr, R., & Spinath, B. (2012). Not all roads lead to Rome—comparing different types of motivational regulation profiles. Learning and Individual Differences, 22, 269–279.CrossRefGoogle Scholar
  139. Shawer, S. F. (2012). Interdisciplinary and intercultural differences in learning strategy use: implications for language processing, curriculum and instruction. Asia Pacific Education Review, 13, 529–540.CrossRefGoogle Scholar
  140. Siegler, R. S. (1996). Emerging minds: the process of change in children’s thinking. New York: Oxford University Press.Google Scholar
  141. Siegler, R. S. (2000). The rebirth of children’s learning. Child Development, 71, 26–35.CrossRefGoogle Scholar
  142. Siegler, R. S., & Jenkins, E. (1989). How children discover new strategies. Hillsdale: Lawrence Erlbaum Associates.Google Scholar
  143. Sikes, P. L. (2013). The effects of specific practice strategy use on university string players’ performance. Journal of Research in Music Education, 61, 318–333.CrossRefGoogle Scholar
  144. Simon, H. A. (1973). The structure of ill structured problems. Artificial Intelligence, 4, 181–201.CrossRefGoogle Scholar
  145. Smemoe, W. B., & Haslam, N. (2013). The effect of language learning aptitude, strategy use and learning context on L2 pronunciation learning. Applied Linguistics, 34, 435–456.CrossRefGoogle Scholar
  146. Sullivan, S., Gnesdilow, D., & Puntambekar, S. (2011). Navigation behaviors and strategies used by middle school students to learn from a science hypertext. Journal of Educational Multimedia and Hypermedia, 20, 387.Google Scholar
  147. Sung, K. Y., & Wu, H. P. (2011). Factors influencing the learning of Chinese characters. International Journal of Bilingual Education and Bilingualism, 14, 683–700.CrossRefGoogle Scholar
  148. Taasoobshirazi, G., & Farley, J. (2013). A multivariate model of physics problem solving. Learning and Individual Differences, 24, 53–62.CrossRefGoogle Scholar
  149. Tang, M., & Tian, J. (2015). Associations between Chinese EFL graduate students’ beliefs and language learning strategies. International Journal of Bilingual Education and Bilingualism, 18, 131–152.CrossRefGoogle Scholar
  150. Tenison, C., Fincham, J. M., & Anderson, J. R. (2014). Detecting math problem solving strategies: an investigation into the use of retrospective self-reports, latency and fMRI data. Neuropsychologia, 54, 41–52.CrossRefGoogle Scholar
  151. Throndsen, I. (2011). Self-regulated learning of basic arithmetic skills: a longitudinal study. British Journal of Educational Psychology, 81, 558–578.CrossRefGoogle Scholar
  152. Tomas, C. (2014). Marking and feedback provision on essay-based coursework: a process perspective. Assessment & Evaluation in Higher Education, 39, 611–624.CrossRefGoogle Scholar
  153. Tsai, Y. R., & Talley, P. C. (2014). The effect of a course management system (CMS)-supported strategy instruction on EFL reading comprehension and strategy use. Computer Assisted Language Learning, 27, 422–438.CrossRefGoogle Scholar
  154. Tuysuzoglu, B. B., & Greene, J. A. (2015). An investigation of the role of contingent metacognitive behavior in self-regulated learning. Metacognition and Learning, 10, 77–98.CrossRefGoogle Scholar
  155. Vaessen, B. E., Prins, F. J., & Jeuring, J. (2014). University students’ achievement goals and help-seeking strategies in an intelligent tutoring system. Computers & Education, 72, 196–208.CrossRefGoogle Scholar
  156. Vanbinst, K., Ghesquière, P., & De Smedt, B. (2012). Numerical magnitude representations and individual differences in children’s arithmetic strategy use. Mind, Brain, and Education, 6, 129–136.CrossRefGoogle Scholar
  157. Vandevelde, S., Van Keer, H., Schellings, G., & Van Hout-Wolters, B. (2015). Using think-aloud protocol analysis to gain in-depth insights into upper primary school children’s self-regulated learning. Learning and Individual Differences, 43, 11–30.CrossRefGoogle Scholar
  158. Vasilyeva, M., Laski, E. V., & Shen, C. (2015). Computational fluency and strategy choice predict individual and cross-national differences in complex arithmetic. Developmental Psychology, 51, 1489–1500.CrossRefGoogle Scholar
  159. Veenman, M. V., Van Hout-Wolters, B. H., & Afflerbach, P. (2006). Metacognition and learning: conceptual and methodological considerations. Metacognition and learning, 1, 3–14.CrossRefGoogle Scholar
  160. Venter, J. C. (2016). Mapping out the future of genomics. Interview by I. Flatow [audio recording]. Science Friday. Science Friday Initiative, New York. Retrieved from: http://www.sciencefriday.com/segments/mapping-out-the-future-of-genomics/
  161. Vermunt, J. D. (1996). Metacognitive, cognitive and affective aspects of learning styles and strategies: a phenomenographic analysis. Higher Education, 31, 25–50.CrossRefGoogle Scholar
  162. Vermunt, J. D. (2005). Relations between student learning patterns and personal and contextual factors and academic performance. Higher Education, 49, 205–234.CrossRefGoogle Scholar
  163. Vermunt, J. D., & Endedijk, M. D. (2011). Patterns in teacher learning in different phases of the professional career. Learning and Individual Differences, 21, 294–302.CrossRefGoogle Scholar
  164. Vos, N., Van Der Meijden, H., & Denessen, E. (2011). Effects of constructing versus playing an educational game on student motivation and deep learning strategy use. Computers & Education, 56, 127–137.CrossRefGoogle Scholar
  165. Warburton, N., & Volet, S. (2013). Enhancing self-directed learning through a content quiz group learning assignment. Active Learning in Higher Education, 14, 9–22.CrossRefGoogle Scholar
  166. Weinert, F. E., & Helmke, A. (1995). Learning from wise mother nature or big brother instructor: the wrong choice as from an…. Educational Psychologist, 30, 135–142.CrossRefGoogle Scholar
  167. White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91, 461–481.CrossRefGoogle Scholar
  168. Wigent, C. A. (2013). High school readers: a profile of above average readers and readers with learning disabilities reading expository text. Learning and Individual Differences, 25, 134–140.CrossRefGoogle Scholar
  169. Wilson, K., & Narayan, A. (2016). Relationships among individual task self-efficacy, self-regulated learning strategy use and academic performance in a computer-supported collaborative learning environment. Educational Psychology, 36, 236–253.CrossRefGoogle Scholar
  170. Winke, P. (2013). An investigation into second language aptitude for advanced Chinese language learning. The Modern Language Journal, 97, 109–130.CrossRefGoogle Scholar
  171. Woods-Groves, S., Therrien, W. J., Hua, Y., & Hendrickson, J. M. (2013). Essay-writing strategy for students enrolled in a postsecondary program for individuals with developmental disabilities. Remedial and Special Education, 34, 131–141.CrossRefGoogle Scholar
  172. Wu, X., Lowyck, J., Sercu, L., & Elen, J. (2013a). Task complexity, student perceptions of vocabulary learning in EFL, and task performance. British Journal of Educational Psychology, 83, 160–181.CrossRefGoogle Scholar
  173. Wu, X., Lowyck, J., Sercu, L., & Elen, J. (2013b). Vocabulary learning from reading: examining interactions between task and learner related variables. European Journal of Psychology of Education, 28, 255–274.CrossRefGoogle Scholar
  174. Wylie, J., Jordan, J. A., & Mulhern, G. (2012). Strategic development in exact calculation: group and individual differences in four achievement subtypes. Journal of Experimental Child Psychology, 113, 112–130.CrossRefGoogle Scholar
  175. Yang, H. C. (2014). Toward a model of strategies and summary writing performance. Language Assessment Quarterly, 11, 403–431.CrossRefGoogle Scholar
  176. Yıldırım, S. (2012). Teacher support, motivation, learning strategy use, and achievement: a multilevel mediation model. The Journal of Experimental Education, 80, 150–172.CrossRefGoogle Scholar
  177. Yoon, H., & Jo, J. W. (2014). Direct and indirect access to corpora: an exploratory case study comparing students’ error correction and learning strategy use in L2 writing. Language Learning & Technology, 18, 96–117.Google Scholar
  178. Zhang, D., Ding, Y., Barrett, D. E., & Xin, Y. P. (2014a). A comparison of strategic development for multiplication problem solving in low-, average-, and high-achieving students. European Journal of Psychology of Education, 29, 195–214.CrossRefGoogle Scholar
  179. Zhang, L., Goh, C. C., & Kunnan, A. J. (2014b). Analysis of test takers’ metacognitive and cognitive strategy use and EFL reading test performance: a multi-sample SEM approach. Language Assessment Quarterly, 11, 76–102.CrossRefGoogle Scholar
  180. Zhou, M., & Xu, Y. (2012). A self-determination approach to understanding Chinese university students’ choice of academic majors. Individual Differences Research, 10, 49–59.Google Scholar
  181. Zusho, A., & Barnett, P. A. (2011). Personal and contextual determinants of ethnically diverse female high school students’ patterns of academic help seeking and help avoidance in English and mathematics. Contemporary Educational Psychology, 36, 152–164.CrossRefGoogle Scholar

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© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Foundations and Secondary EducationUniversity of North FloridaJacksonvilleUSA

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