Goal-oriented Planning with Technology

1. Bransford, J. D., Brown, A. L., and Cocking, R. R. (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.

2. Breslow, L., Klopfer, E., Moag, N., and Sclar, M. (2013). "Studying learning in the worldwide classroom: Research into edX's first MOOC." Research & Practice in Assessment 8(1): 13-25.

3. Burd, E., Stacey, M., and Seaman, J. (2015). Business models for MOOCs: A literature review. Innovative Higher Education, 40(1), 37-49.

4. Ceballos, A., et al. (2011). "A goal-oriented autonomous controller for space exploration." In Proceedings of the ASTRA Conference on Artificial and Synthetic Intelligence Research in Astronautics, 11(9), 3661-3667.

5. Deci, E. L., and Ryan, R. M. (1985). Intrinsic and extrinsic motivations: Classification of motives and regulation ofcognitions, emotions, and behaviors. Integrative Psychological and Physiological Processes, 17(3), 260-276.

6. Dobbin, F. (2009). Inventing Equal Opportunity: America's Schools in the Twentieth Century. Princeton, NJ: Princeton University Press.

7. Riel, J., and Lawless, K. A. (2017). Developments in MOOC technologies and participation since 2012. In Handbook of E-Learning II (pp. 439-468). Springer International Publishing.

8. Song, H.-D., and Grabowski, B. L. (2006). Stimulating intrinsic motivation for problem solving using goal-oriented contexts and peer group composition. Educational Technology Research and Development, 54(5), 445-466.

9. Tomlinson, C. A., and McTighe, J. (2006). Integrating differentiated instruction with Understanding by Design: Connecting content and kids. Alexandria, VA: Association for Supervision and Curriculum Development.

10. Toven-Lindsey, B., Pardo, L., Gross, A. L., Guo, X., Kim, J., Koedinger, J. (2015). Virtually unlimited classrooms: Pedagogical practices in massive open online courses. The Internet and Higher Education, 24, 1-12.

11. Welsh, S. L. (2005). Goal-oriented personal learning plans and their effect on student aspirations regarding post-secondary education. Unpublished doctoral dissertation, Boston College.

12. Yoganarasimhan, H. (2019). Search Personalization Using Machine Learning. Management Science.

13. Ysseldyke, J. E., and McLeod, S. (2007). Using technology tools to monitor response to intervention. In N. K. Glover & M. A. Kuchler (Eds.), Handbook of Response to Intervention (RTI) (pp. 395-417). New York: Springer.

These references cover a range of topics from the foundations of learning and motivation to the specific application of MOOCs in education. They include seminal works on how people learn, motivational theories, the impact of technology on learning, and the evolution and pedagogy of massive open online courses (MOOCs). The list also includes a literature review on business models for MOOCs, which is relevant given the economic and operational considerations of such platforms. Additionally, it touches upon the psychological aspects of motivation and goal-setting in learning, as well as practical applications like differentiated instruction and response to intervention strategies. Finally, it references recent advancements in search personalization using machine learning, which can impact how educational content is delivered and tailored to individual learners' needs.