A burgeoning research literature shows that students who value learning and believe success is within reach persist in the face of failure, excel academically, and accomplish more than people who don’t, even if they are equal in ability levels.  (see A. Bandura on Self-Efficacy; Attribution and Social Expectancy Theories, C. Dweck on Self-Theories and Mindset; A. Duckworth on Grit; D. McClelland on Acquired Need for Achievement; W. Mischel on Self-Control). Yet, little is known about whether students view learning as their primary goal in school, whether their goals vary by context or academic performance level, and whether their goals carry predictive power for academic performance. This gap is unfortunate because if students do not have learning as a primary goal, no amount of instruction will improve their learning. These projects examine how students’ understanding of their own goals, goals set by their schools, and their teachers impact their learning and problem solving across a range of challenging domains.

Related Publications:

• Lin-Siegler, X. D. Shaenfield, D. & Elder, A.  (2015). Contrasting case instruction can improve self-assessment of writing.  Educational Technology Research & Development, 63 (4), 517-537.
• Sullivan, F. R. & Lin-Siegler, X. D. (2012). The ideal science student: Exploring the relationship of students’ perceptions to their problem solving activities in a robotics context. Journal of Interactive Learning Research, 23(3), 273-308.
• Siegler, R., & Lin, X. D. (2010). Self-explanations promote children’s learning. In S. H. Waters & W. Schneider (Eds.), Metacognition, strategy use and instruction (Chapter 4, pp. 85-113). New York, NY: The Guilford Press.
• Lin, X. D., & Sullivan, F. (2008). Computers as metacognitive tools. In J. Voogt & G. Knezek (Eds.), International handbook of education and technology (pp. 281-298). New York, NY: Springer.
• Wang, Y., Dogan, E., & Lin, X. D. (2006). Effect of multiple-perspective thinking on problem solving. In Proceedings of the 7th International Conference on Learning Sciences, pp.812-817. Bloomington, Indiana, International Society of the Learning Sciences.
• Schwartz. D.L., Lin, X.D., Brophy, S., & Bransford, J.D. (1999). Toward the development of flexibly adaptive instructional designs. In C. M. Reigeluth (Eds.), Instructional Design Theories and Models, Vol. II. (pp. 183-213). Mahwah, NJ: Lawrence Erlbaum Associates.
• Lin, X.D., Schwartz, D., & Hatano, G. (2005). Toward teachers’ adaptive metacognition. Educational Psychologist, 40(4), 245-255.
• Lin, X.D., & Hatano, G. (2003). Technology, culture and adaptive mind. Mind, Culture & Activity. 10(1), 3-8.
• Lin, X.D., & Schwartz, D. (2003). Reflection at the crossroad of cultures. Mind, Culture & Activity, 10(1), 9-25.
• Lin, X. (2001). Designing metacognitive activities. Educational Technology Research and Development, 49(2), 23-40.
• Hmelo, C. E. & Lin, X. D. (2000). Becoming self-directed learners: Strategy development in problem-based learning. In D. Evensen & C. E. Hmelo (Eds.), Problem-based learning: Research perspectives on learning interactions (pp.227-250). Mahwah NJ: Erlbaum.
• Lin, X.D. (1994). Metacognition: Implications for design and research in a hypermedia-based learning environment. In Proceedings of Selected Research and Development Presentations at the 1994 National Convention of the Association of Educational Communication and Technology, pp. 483-502, Nashville, TN.
• Lin, X.D. (1994). Embedding metacognitive cues in the hypermedia system to promote far transfer problem solving. In Proceedings of Selected Research and Development Presentations at the 1994 National Convention of the Association of Educational Communication and Technology, pp. 463-482, Nashville, TN.
• Moore, J.L., Lin, X.D., Schwartz, D.L., Petrosino, A., Hickey, D.T., & Campbell, J.O. (1994). The relationship between situated cognition and anchored instruction: A response to Tripp. Educational Technology, 8, 28-32.