Дистанционное обучение с позиции наук об учении. Часть 1
https://doi.org/10.31992/0869-3617-2021-30-2-33-49
Аннотация
В литературе продолжаются дискуссии о концептуальных основаниях дистанционного обучения. Учёные рассматривают различные теоретические точки зрения, включая, помимо прочего, теорию независимости и автономии, теорию индустриализации и теорию взаимодействия и коммуникации, через призму традиционного подхода к теории обучения. Отсутствует обсуждение потенциальной роли недавно появившейся области – науки об учении (Learning Sciences) – в формировании теории дистанционного обучения. Таким образом, в этой статье мы предлагаем теоретический анализ направления наук об учении как нового подхода к пониманию дистанционного обучения в эпоху информационных и коммуникационных технологий (ИКТ). Эта инновационная область, изучающая преподавание и учение, включает, среди прочих, несколько дисциплин, таких как когнитивная наука, педагогическая психология, антропология, информатика и многие другие. Основная цель Learning Sciences – изучение и разработка эффективной обучающей среды, включая дистанционное обучение, на основе последних данных о процессах, связанных с тем, как человек познаёт и учится.
Ключевые слова
Об авторе
М. А. Чошанов
Техасский университет в Эль Пасо
Соединённые Штаты Америки
Соединённые Штаты Америки
Чошанов Мурат Аширович – PhD, проф., кафедра высшей математики и кафедра подготовки учителей
EDU612, 500 W. University Avenue, El Paso, TX 79968
Список литературы
1. Herek, G. (1995). Developing a Theoretical Framework and Rationale for a Research Proposal. In: Pequegnat, W., Stover, E. (Eds.). How to Write a Successful Research Grant Application: A Guide for Social and Behavioral Scientists. Norwell, MA: Kluwer, pp. 85-91.
2. Anderson, T., Dron, J. (2011). Three Generations of Distance Education Pedagogy. International Review of Research in Open & Distance Learning. Vol. 12, no. 3, pp. 88-97, doi: 10.19173/irrodl.v12i3.890
3. Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age. International Journal of Instructional Technology & Distance Learning. Vol. 2, no. 1, pp. 3-10. Available at: https://jotamac.typepad.com/jotamacs_weblog/files/Connectivism.pdf (accessed 07.01.21).
4. Simonson, M., Smaldino, S., Albright, M., Zvacek, S. (2006). Teaching and Learning at a Distance (3rd edition ed.). Upper Saddle River, New Jersey: Pearson Prentice Hall, 241 p.
5. Gunawardena, C.N., McIsaac, M.S. (2003). Distance education. In: Jonassen, D. (Ed.). Handbook for Research on Educational Communications and Technology. New York: Simon and Schuster, pp. 355-396.
6. Peters, O. (2001). Learning and Teaching in Distance Education. Analysis and Interpretations from an International Perspective. London: Kogan Page, 268 p.
7. Holmberg, B. (1987). The development of distance education research. The American Journal of Distance Education. Vol. 1, no. 3, pp. 16-23. Available at: https://www.learntechlib.org/p/139179/ (accessed 07.01.21).
8. Clark, R.C., Mayer, R.E. (2003). E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. San Francisco: Jossey-Bass, 322 p.
9. Sapunov, M.B., Polonnikov, A.A. (2018). Academic Subject Problem: Epistemological Crisis and Its Overcoming. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 27, no. 12, pp. 144-157, doi: https://doi.org/10.31992/0869-3617-2018-27-12-144-157 (In Russ., abstract in Eng.).
10. Babaeva, M.A., Golubev, E.B. (2020). «Talgenism» in the Digital Age: A Domestic History of cMOOC. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 29, no. 8-9, pp. 71-84, doi: https://doi.org/10.31992/0869-3617-2020-29-8-9-71-84 (In Russ., abstract in Eng.).
11. Sawyer, K. (Ed.) (2014). The Cambridge Handbook of the Learning Sciences. Cambridge: Cambridge University Press, 648 p.
12. Bransford, J., Brown, A., Cocking, R. (Eds.). (2000). How People Learn: Brain, Mind, Experience, and School. Washington, DC: National Academy Press, pp. 206-230. Available at: https://www.ncbi.nlm.nih.gov/books/NBK223290/ (accessed 07.01.21).
13. Donovan, M., Bransford, J. (2005). How Students Learn: History, Mathematics, and Science in the Classroom. National Research Council Report. Washington, DC: National Academy Press, 336 p.
14. Valverde, Y., Tchoshanov, M. (2013). Secondary Mathematics Teachers’ Disposition Toward Challenge and its Effect on Teaching Practice and Student Performance. Kazanskiy pedagogicheskiy zhurnal = Kazan Pedagogical Journal. Vol. 3, pp. 25-33. Available at: https://kp-journal.ru/wp-content/uploads/2017/02/2013-3.pdf (accessed 07.01.21).
15. Bruer, J. (1993). Schools for Thought: A Science of Learning in the Classroom. Cambridge, MA: MIT Press, 336 p.
16. Caine, R., Caine G. (1994). Making Connections. Teaching and the Human Brain. Menlo Park, CA: Addison Wesley.
17. Chabris, C., Kosslyn, S. (1998). How Do the Cerebral Hemispheres Contribute to Encoding Spatial Relations? Current Directions in Psychology. Vol. 7, no. 1, pp. 8-14, doi: https://psycnet.apa.org/doi/10.1111/1467-8721.ep11521809
18. Dehaene, S. (1996). The Organization of Brain Activations in Number Comparison. Journal of Cognitive Neuroscience. Vol. 8, no. 1, pp. 47-68, doi: https://psycnet.apa.org/doi/10.1162/jocn.1996.8.1.47
19. Posner, M., Raichle, M. (1994). Images of Mind. N.Y.: Scientific American Library, 257 p.
20. Jensen, E. (2005). Teaching with the Brain in Mind. 2nd edition. Alexandria, VA: ASCD, 187 p.
21. Sousa, D. (1995). How the Brain Learns: A Classroom Teacher’s Guide. Reston, VA: NASSP, 143 p.
22. Springer, S., Deutsch G. (1993). Left Brain, Right Brain. N.Y.: W.H. Freeman, 368 p.
23. Sylwester, R. (1995). A Celebration of Neurons. Alexandria, VA: ASCD, 167 p.
24. Vygotsky, L.S. (1978) Mind in Society: The Development of Higher Psychological Processes. Cambridge: Harvard University Press. 176 p.
25. Ambrose, S.A., Bridges, M.W., DiPietro, M., Lovett, M.C., Norman, M.K. (2010). How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco, CA: Jossey-Bass, 301 p. Available at: https://firstliteracy.org/wp-content/uploads/2015/07/How-LearningWorks.pdf (accessed 07.01.21).
26. Metcalfe, J., Kornell, N. (2005). A Region or Proximal of Learning Model of Study Time Allocation. Journal of Memory and Language. Vol. 52, no. 4, pp. 463-477, doi: https://psycnet.apa.org/doi/10.1016/j.jml.2004.12.001
27. Wolfe, P., Brandt R. (1998). What Do We Know from Brain Research? Educational Leadership. vol. 56, no. 3, pp. 8-13. Available at: http://www.ascd.org/publications/educational-leadership/nov98/vol56/num03/What-Do-We-Knowfrom-Brain-Research%C2%A2.aspx (accessed 07.01.21).
28. Harp, S.F., Mayer, R.E. (1998). How Seductive Details Do Their Damage: A Theory of Cognitive Interest in Science Learning. Journal of Educational Psychology. Vol. 90, no. 3, pp. 414-434, doi: https://psycnet.apa.org/doi/10.1037/0022-0663.90.3.414
29. Mautone, P.D., Mayer, R.E. (2001). Signaling as a Cognitive Guide in Multimedia Learning. Journal of Educational Psychology. Vol. 93, no. 2, pp. 377-389, doi: https://psycnet.apa.org/doi/10.1037/0022-0663.93.2.377
30. Mayer, R.E. (2010). Applying the Science of Learning. Boston, MA: Pearson. 144 p.
31. Kalyuga, S., Chandler, P., Tuovinen, J., Sweller, J. (2001). When Problem Solving is Superior to Studying Worked Examples. Journal of Educational Psychology. Vol. 93, no. 3, pp. 579–588, doi: https://psycnet.apa.org/doi/10.1037/0022-0663.93.3.579
32. Rouet, J. (2006). The Skills of Document Use: From Text Comprehension to Web-Based Learning. Mahwah, NJ: Erlbaum, 248 p.
33. Spiro, R.J., Feltovich, P.J., Jacobson, M.J., Coulson, R.C. (1991). Cognitive Flexibility, Constructivism, and Hypertext: Random Access Instruction for Advanced Knowledge Acquisition in Ill-Structured Domains. Educational Technology. Vol. 31, no. 5, pp. 24-33. Available at: http://www.jstor.org/stable/44427517 (accessed 07.01.21).
34. Johnson, D.W., & Johnson, R.T. (2009). An Educational Psychology Success Story: Social Interdependence Theory and Cooperative Learning. Educational Researcher. Vol. 38, no. 5, pp. 354-379, doi: https://doi.org/10.3102%2F0013189X09339057
35. Karau, S., Williams, K. (1993). Social Loafing: A Meta-Analytic Review and Theoretical Integration. Journal of Personality and Social Psychology. Vol. 65, pp. 681-706, doi: https://doi.org/10.1037/0022-3514.65.4.681
36. Hodara, M. (2011). Reforming Mathematics Classroom Pedagogy: Evidence-Based Findings and Recommendations for the Developmental Math Classroom. Community College Research Center, New York, NY. Working Paper No. 27. Available at: https://ccrc.tc.columbia.edu/media/k2/attachments/reforming-mathematicsclassroom-pedagogy.pdf (accessed 07.01.21).
37. Mayer, R.E., Moreno, R. (2003). Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist. Vol. 38, no. 1, pp. 43-52. Available at: https://faculty.washington.edu/farkas/WDFR/MayerMoreno9WaysToReduceCognitiveLoad.pdf (accessed 07.01.21).
38. Bereiter, C., Scardamalia, M. (1985). Cognitive Coping Strategies and the Problem of “Inert Knowledge”. In: Chipman, S.F., Segal, J.W., Glaser, R. (Eds.). Thinking and Learning Skills. Vol. 2. Current research and open questions. Hillsdale, NJ: Erlbaum. pp. 65-80.
39. Bjork, R.A. (1988). Retrieval Practice and Maintenance of Knowledge. In: Gruneberg, M.M., Morris, P.E., & Sykes, R.N. (Eds.). Practical Aspects of Memory: Current Research and Issues. Vol. 1. NY: Wiley, pp. 396-401.
40. Chinn, C.A., & Brewer, W.F. (1998). An Empirical Test of a Taxonomy of Responses to Anomalous Data in Science. Journal of Research in Science Teaching. Vol. 35, no. 6, pp. 623-654, doi: https://psycnet.apa.org/doi/10.1002/(SICI)1098-2736(199808)35:6%3C623::AID-TEA3%3E3.0.CO;2-O
41. Eryilmaz, A. (2002). Effects of Conceptual Assignments and Conceptual Change Discussions on Students’ Misconceptions and Achievement Regarding Force and Motion. Journal of Research in Science Teaching. Vol. 39, no. 10, pp. 1001- 1015, doi: https://doi.org/10.1002/tea.10054
42. Guzzetti, B. J. (2000). Learning Counter-Intuitive Science Concepts: What Have We Learned from over a Decade of Research? Reading & Writing Quarterly. Vol. 16, no. 2, pp. 89-98, doi: https://psycnet.apa.org/doi/10.1080/105735600277971
43. Hynd, C.R. (2001). Refutational Texts and the Change Process. International Journal of Educational Research. Vol. 35, no. 7-8, pp. 699-714, doi: 10.1016/s0883-0355(02)00010-1
44. Salden, R., Alaven, V., Renkl, A., Schwonke, R. (2009). Worked Examples and Tutored Problem Solving: Redundant or Synergistic Forms of Support? Topics in Cognitive Science. Vol. 1, pp. 203-213, doi: https://doi.org/10.1111/j.1756-8765.2008.01011.x
45. Schworm, S., Renkl, A. (2002). Learning by Solved Example Problems: Instructional Explanations Reduce Self-Explanation Activity. In: Gray, W.D. Schunn, C.D. (Eds.). Proceedings of the 24th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum, pp. 816-821.
46. Trafton, J.G., Reiser, B.J. (1993). The Contributions of Studying Examples and Solving Problems to Skill Acquisition. In: Polson, M. (Ed.). Proceedings of the 15th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum, pp. 1017-1022.
47. Craig, S.D., Sullins, J., Witherspoon, A., Gholson, B. (2006). The Deep-Level-Reasoning-Question Effect: The Role of Dialogue and Deep-LevelReasoning Questions During Vicarious Learning. Cognition and Instruction, vol. 24, no. 4, pp. 565-591, doi: https://psycnet.apa.org/doi/10.1207/s1532690xci2404_4
48. Graesser, A.C., Person, N.K. (1994). Question Asking During Tutoring. American Educational Research Journal, vol. 31, no. 1, pp.104-137, doi: https://psycnet.apa.org/doi/10.2307/1163269
49. Pressley, M., Wood, E., Woloshyn, V.E., Martin, V., King, A., Menke, D. (1992). Encouraging Mindful Use of Prior Knowledge: Attempting to Construct Explanatory Answers Facilitates Learning. Educational Psychologist. Vol. 27, no. 1, pp. 91-109, doi: https://psycnet.apa.org/doi/10.1207/s15326985ep2701_7
50. Arum, R., Roksa, J. (2011). Limited Learning on College Campuses. Society. Vol. 48, 203, doi: https://doi.org/10.1007/s12115-011-9417-8
51. Butler, A.C., Roediger, H.L. (2007). Testing Improves Long-Term Retention in a Simulated Classroom Setting. European Journal of Cognitive Psychology. Vol. 19, no. 4-5, pp. 514–527, doi: https://doi.org/10.1080/09541440701326097
52. Dempster, F.N. (1997). Distributing and Managing the Conditions of Encoding and Practice. In: Bjork, E.L. Bjork, R.A. (Eds.). Human Memory. San Diego, CA: Academic Press, pp. 197-236.
53. Pyc, M.A., Rawson, K.A. (2010). Why Testing Improves Memory: Mediator Effectiveness Hypothesis. Science. Vol. 330, issue 6002, p. 335, doi: 10.1126/science.1191465
54. Black, P., Harrison, C., Lee, C., Marshall, B., Wiliam, D. (2003). Assessment for Learning: Putting it into Practice. Buckingham, UK: Open University Press, 152 p.
55. Kulik, J.A., Kulik, C.C. (1988). Timing of Feedback and Verbal Learning. Review of Educational Research. Vol. 58, no. 1, pp. 79-97, doi: https://doi.org/10.3102%2F00346543058001079
56. Williams, L. (1983). Teaching for the Two-Sided Mind. A Guide for Right Brain/Left Brain Education. N.Y.: A Touchstone Book, 213 p.
57. Savinainen, A., Scott, P. (2002). The Force Concept Inventory: A Tool for Monitoring Student Learning. Physics Education. Vol. 37, no. 1, pp. 45-52, doi: https://www.per-central.org/items/Load.cfm?ID=2865
58. American Psychological Association. (2011). Modules for Teachers: How Do I Get My Students over Their Alternative Conceptions (Misconceptions) for Learning. Available at: http://apa.org/education/k12/misconceptions.aspx (accessed 08.01.21).
59. Ainsworth, S., Loizou, A.T. (2003). The Effects of Self-Explaining When Learning with Texts or Diagrams. Cognitive Science. Vol. 27, pp. 669-681, doi: 10.1016/S0364-0213(03)00033-8
60. Chi, M.T.H., Bassok, M., Lewis, M., Reimann, P., Glaser, R. (1989). Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science. Vol. 13, no. 2, pp. 145-182, doi: https://doi.org/10.1016/0364-0213(89)90002-5
61. De Bruin, A., Rikers, R., Schmidt, H. (2007). The Effect of Self-Explanation and Prediction on the Development of Principled Understanding of Chess in Novices. Contemporary Educational Psychology. Vol. 32, no. 2, pp. 188-205, doi: https://doi.org/10.1016/j.cedpsych.2006. 01.001
62. Griffin, T.D., Wiley, J., Thiede, K.W. (2008). Individual Difference, Rereading, and SelfExplanation: Concurrent Processing and Cue Validity as Constraints on Metacomprehension Accuracy. Memory & Cognition. Vol. 36, no. 1, pp. 93-103, doi: https://psycnet.apa.org/doi/10.3758/MC.36.1.93
63. Roscoe, R.D., Chi, M.T.H. (2008). Tutor Learning: The Role of Explaining and Responding to Questions. Instructional Science. Vol. 36, pp. 321-350, doi: https://doi.org/10.1007/s11251-007-9034-5
64. Blerkom, M.L., Blerkom, D.L. (2004). Self-Monitoring Strategies Used by Developmental and Non-Developmental College Students. Journal of College Reading and Learning. Vol. 34, no. 2, pp. 45-60, doi: https://doi.org/10.1080/10790195.2004.10850161
65. Brown, D., Frank, A.R. (1990). “Let Me Do It”: Self-Monitoring in Solving Arithmetic Problems. Education & Treatment of Children. Vol. 13, no. 3, pp. 239-248.
66. Chang, M. (2007). Enhancing Web-Based Language Learning through Self-Monitoring. Journal of Computer Assisted Learning. Vol. 23, no. 3, pp. 187-196, doi: https://doi.org/10.1111/j.1365-2729.2006.00203.x
67. Zimmerman, B.J. (2001). Theories of Self-Regulated Learning and Academic Achievement: An Overview and Analysis. In: Zimmerman, B.J., Schunk, D.H. (Eds.). Self-Regulated Learning and Academic Achievement. 2nd ed. Hillsdale, NJ: Erlbaum, pp. 1-38.
68. Smith, S.M., Vela, E. (2001). Environmental Context-Dependent Memory: A Review and Meta-Analysis. Psychonomic Bulletin & Review. Vol. 8, pp. 203-220, doi: https://doi.org/10.3758/BF03196157
69. Rohrer, D. (2009). The Effects of Spacing and Mixing Practice Problems. Journal for Research in Mathematics Education. Vol. 40, pp. 4-17. Available at: http://www.jstor.org/stable/40539318 (accessed 08.01.2021).
70. Capeda, N.J., Vul, E., Rohrer, D., Wixted, J.T., Pashler, H. (2008). Spacing Effects in Learning: A Temporal Ridgeline of Optimal Retention. Psychological Science. Vol. 19, no. 11, pp. 1095- 1102, doi: https://doi.org/10.1111%2Fj.1467-9280.2008.02209.x
71. Kornell, N. (2009). Optimising Learning Using Flashcards: Spacing Is More Effective Than Cramming. Applied Cognitive Psychology, vol. 23, pp. 1297-1317, doi: 10.1002/acp.1537
72. Ericsson, K.A., Krampe, R.T., Tescher-Romer, C. (2003). The Role of Deliberate Practice in the Acquisition of Expert Performance. Psychological Review. Vol. 100, no. 3, pp. 363-406, Available at: https://graphics8.nytimes.com/images/blogs/freakonomics/pdf/DeliberatePractice(PsychologicalReview).pdf (accessed 08.01.2021).
73. Rothkopf, E.Z., Billington, M.J. (1979). GoalGuided Learning from Text: Inferring a Descriptive Processing Model from Inspection Times and Eye Movements. Journal of Educational Psychology. Vol. 71, no. 3, pp. 310-327, doi: https://psycnet.apa.org/doi/10.1037/0022-0663.71.3.310
74. Szupnar, K.K., McDermott, K.B., Roediger, H.L. (2007). Expectation of a Final Cumulative Test Enhances Long-Term Retention. Memory & Cognition. Vol. 35, pp. 1007-1013, doi: https://doi.org/10.3758/BF03193473
75. Tchoshanov, M. (2013). Engineering of Learning: Conceptualizing e-Didactics. Moscow: UNESCO IITE. 192 p.
Рецензия
Просмотров:
1350
Послать статью по эл. почте 