Sequential patterns of affective states of novice programmers

CEUR Workshop Proceedings

Volumn 1009, Issue , 2013, Pages 1-10

  Bosch, Nigel ^a   D'Mello, Sidney ^a  

^a UNIVERSITY OF NOTRE DAME   (United States)

Author keywords

Affect; Computer programming; Computerized learning; Sequences

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEMS PROGRAMMING; EDUCATION; EDUCATION COMPUTING; SCAFFOLDS; STUDENTS;

AFFECT; COMPUTERIZED LEARNING; PERFORMANCE OUTCOME; PROGRAMMING EDUCATION; PROGRAMMING EXERCISE; PROGRAMMING EXPERIENCE; SEQUENCES; THEORETICAL MODELING;

COMPUTER PROGRAMMING;

EID: 84924967667     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Haungs, M., Clark, C., Clements, J., Janzen, D.: Improving first-year success and retention through interest-based CS0 courses. Proceedings of the 43rd ACM technical symposium on Computer Science Education. pp. 589-594. ACM, New York, NY, USA (2012).
2. Fossati, D., Di Eugenio, B., Brown, C.W., Ohlsson, S., Cosejo, D.G., Chen, L.: Supporting Computer Science Curriculum: Exploring and Learning Linked Lists with iList. IEEE Transactions on Learning Technologies. 2, 107-120 (2009).
3. Anderson, J.R., Skwarecki, E.: The automated tutoring of introductory computer programming. Communications of the ACM. 29, 842-849 (1986).
4. Brusilovsky, P., Sosnovsky, S., Yudelson, M.V., Lee, D.H., Zadorozhny, V., Zhou, X.: Learning SQL programming with interactive tools: From integration to personalization. ACM Transactions on Computing Education. 9, 19:1-19:15 (2010).
5. Cheung, R., Wan, C., Cheng, C.: An ontology-based framework for personalized adaptive learning. Advances in Web-Based Learning-ICWL 2010. pp. 52-61. Springer, Berlin Heidelberg (2010).
6. Hsiao, I.-H., Sosnovsky, S., Brusilovsky, P.: Guiding students to the right questions: adaptive navigation support in an E-Learning system for Java programming. Journal of Computer Assisted Learning. 26, 270-283 (2010).
7. Pekrun, R.: The impact of emotions on learning and achievement: Towards a theory of cognitive/motivational mediators. Applied Psychology. 41, 359-376 (1992).
8. Grafsgaard, J.F., Fulton, R.M., Boyer, K.E., Wiebe, E.N., Lester, J.C.: Multimodal analysis of the implicit affective channel in computer-mediated textual communication. Proceedings of the 14th ACM international conference on Multimodal interaction. pp. 145-152. ACM, New York, NY, USA (2012).
9. Lee, D.M.C., Rodrigo, M.M.T., Baker, R.S.J. d, Sugay, J.O., Coronel, A.: Exploring the relationship between novice programmer confusion and achievement. In: D'Mello, S., Graesser, A., Schuller, B., and Martin, J.C. (eds.) Affective Computing and Intelligent Interaction. pp. 175-184. Springer, Berlin Heidelberg (2011).
10. Rodrigo, M.M.T., Baker, R.S.J. d, Jadud, M.C., Amarra, A.C.M., Dy, T., Espejo-Lahoz, M.B.V., Lim, S.A.L., Pascua, S.A.M.S., Sugay, J.O., Tabanao, E.S.: Affective and behavioral predictors of novice programmer achievement. SIGCSE Bulletin. 41, 156-160 (2009).
11. D'Mello, S., Graesser, A.: Feeling, thinking, and computing with affect-aware learning technologies. In: Calvo, R.A., D'Mello, S., Gratch, J., and Kappas, A. (eds.) Handbook of Affective Computing. Oxford University Press (in press).
12. D'Mello, S., Lehman, B., Sullins, J., Daigle, R., Combs, R., Vogt, K., Perkins, L., Graesser, A.: A time for emoting: When affect-sensitivity is and isn't effective at promoting deep learning. In: Aleven, V., Kay, J., and Mostow, J. (eds.) Intelligent Tutoring Systems. pp. 245-254. Springer, Berlin Heidelberg (2010).
13. Forbes-Riley, K., Litman, D.: Benefits and challenges of real-time uncertainty detection and adaptation in a spoken dialogue computer tutor. Speech Communication. 53, 1115-1136 (2011).
14. Khan, I.A., Hierons, R.M., Brinkman, W.P.: Mood independent programming. Proceedings of the 14th European Conference on Cognitive Ergonomics: Invent! Explore! pp. 28-31. ACM, New York, NY, USA (2007).
15. Bosch, N., D'Mello, S., Mills, C.: What Emotions Do Novices Experience During their First Computer Programming Learning Session? Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013) (in press).
16. D'Mello, S., Graesser, A.: Dynamics of affective states during complex learning. Learning and Instruction. 22, 145-157 (2012).
17. D'Mello, S., Lehman, B., Pekrun, R., Graesser, A.: Confusion can be beneficial for learning. Learning and Instruction. (in press).
18. Inventado, P.S., Legaspi, R., Cabredo, R., Numao, M.: Student learning behavior in an unsupervised learning environment. Proceedings of the 20th International Conference on Computers in Education. pp. 730-737. National Institute of Education, Singapore (2012).
19. McQuiggan, S.W., Robison, J.L., Lester, J.C.: Affective transitions in narrative-centered learning environments. In: Woolf, B.P., Aïmeur, E., Nkambou, R., and Lajoie, S. (eds.) Intelligent Tutoring Systems. pp. 490-499. Springer, Berlin Heidelberg (2008).
20. Rosenberg, E.L., Ekman, P.: Coherence between expressive and experiential systems in emotion. Cognition & Emotion. 8, 201-229 (1994).
21. D'Mello, S., Taylor, R.S., Graesser, A.: Monitoring affective trajectories during complex learning. Proceedings of the 29th annual meeting of the cognitive science society. pp. 203-208. Cognitive Science Society, Austin, TX (2007).