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Editors’ Note

Paving New Pathways to Supporting Disciplinary Learning

The closing issue of volume 24 of the Journal of the Learning Sciences features some recent innovations in research on fostering disciplinary learning. Research in the learning sciences often focuses on improving our understanding of what kinds of practices and reasoning characterize a domain, and using this knowledge to design supportive learning environments. The articles in this issue continue this tradition, and they also reflect some recent advances in the field: exploring the interplay between cognition and affect in disciplinary reasoning, and incorporating gaming as part of formal disciplinary learning.

The first two articles examine mathematical learning through emotional and cognitive lenses. Though educational research is replete with depictions of the emotional upheavals of math anxiety, these articles seek to build a more explicit connection between mathematical practices and the mechanisms by which learners develop self-concepts and affective attachments. Heyd-Metzuyanim (Citation2015/Citationthis issue) follows Sfard’s work on “commognition” (Sfard, Citation2007), highlighting processes by which learners come to identify as being mathematically competent or incompetent through engagement with particular math topics. The findings suggest that math-related self-concepts are dynamic and modular, and can vary not just across time and contexts, but also across specific topics, exemplifying the interrelatedness between the content and structure of mathematics as a domain and the affective dimensions of the learner. Sengupta-Irving and Enyedy (Citation2015/Citationthis issue) also demonstrate how affective responses mediate learners’ engagement in the domain. Their study compares the affective responses experienced in student-driven and teacher-driven pedagogical designs, and details ways these responses relate to specific mathematical practices on the one hand and to specific learning-environment designs on the other.

The third and fourth articles in this issue use game designs as a lens through which to study disciplinary learning. Martin et al. (Citation2015/Citationthis issue) use data mining as an analytical tool for fine-grained analysis of students’ learning paths while engaging in an online game, identifying ways the mathematical practice of “splitting” (partitioning a whole into equal parts) develops through game play. The study is part of a growing trend in learning sciences research: using learning analytics to inspect large-scale data sets in order to document fine-grained learning processes (e.g., Martin & Sherin, Citation2013; Blikstein, Worsely, Piech, Sahami, Cooper, & Koller, Citation2014; Roll, Baker, Aleven, & Koedinger, Citation2014).

Sengupta, Krinks, and Clark (Citation2015/Citationthis issue) also leverage game design to study disciplinary learning, building on a rich tradition in examining conceptual change in physics. Their microgenetic analysis, using clinical interviews strategically between game levels, contributes to ongoing efforts in the field to strike a balance between detailed documentation of gamers’ thinking, and allowing for the uninterrupted flow that is characteristic of game-based learning. The article offers implications for the design of conceptually integrated games to support disciplinary learning.

As we conclude volume 24 of JLS, the editorial board and editorial team of the journal would like to take this opportunity to thank reviewers for their essential role in sustaining and advancing the journal. One of the central values of JLS is to maintain an editorial process that is not focused on gatekeeping, but rather on collaborating with authors to produce the best possible manuscripts, while maintaining high standards for innovation, contribution to the field, theoretical depth, and methodological rigor. We aim to provide authors with detailed and generative reviews, and make special efforts towards mentoring early career scholars. Reviewers are essential for meeting these goals. In recent editorial board meetings, the important contributions of JLS reviewers were noted, as well as the fact that this volunteer service mainly goes unrecognized.

This issue therefore marks the first of what will be an annual recognition: JLS Reviewer of the Year. This designation is awarded to reviewers who complete multiple reviews for the journal in a timely and thorough fashion, while maintaining the depth, quality, and supportive mentoring that JLS is known for. We also offer a specific appreciation for scholars whose reviewing shows these qualities during the early career period. Please see the JLS Reviewer of the Year Recognition for the two JLS Reviewers of the Year for 2015!

Iris Tabak and Josh Radinsky

Co-Editors-in-Chief

REFERENCES

  • Blikstein, P., Worsley, M., Piech, C., Sahami, M., Cooper, S., & Koller, D. (2014). Programming pluralism: Using learning analytics to detect patterns in the learning of computer programming. Journal of the Learning Sciences, 23, 561–599. doi:10.1080/10508406.2014.954750
  • Heyd-Metzuyanim, E. (2015 /this issue). Vicious cycles of identifying and mathematizing: A case study of the development of mathematical failure. Journal of the Learning Sciences, 24, 504–549. doi:10.1080/10508406.2014.999270
  • Martin, T., Petrick Smith, C., Forsgren Velasquez, N., Aghababyan, A., Janisiewicz, P., & Baker, S. (2015 /this issue). Learning fractions by splitting: Using learning analytics to illuminate the development of mathematical understanding. Journal of the Learning Sciences, 24, 593–637. doi:10.1080/10508406.2015.1078244
  • Martin, T., & Sherin, B. (2013). Learning analytics and computational techniques for detecting and evaluating patterns in learning: An introduction to the special issue. Journal of the Learning Sciences, 22, 511–520. doi:10.1080/10508406.2013.840466
  • Roll, I., Baker, R. S. D., Aleven, V., & Koedinger, K. R. (2014). On the benefits of seeking (and avoiding) help in online problem-solving environments. Journal of the Learning Sciences, 23, 537–560. doi:10.1080/10508406.2014.883977
  • Sengupta, P., Krinks, K., & Clark, D. (2015 /this issue). Learning to deflect: Conceptual change in physics during digital game play. Journal of the Learning Sciences, 24, 638–674. doi:10.1080/10508406.2015.1082912
  • Sengupta-Irving, T., & Enyedy, N. (2015 /this issue). Why engaging in mathematical practices may explain stronger outcomes in affect and engagement: Comparing student-driven with highly guided inquiry. Journal of the Learning Sciences, 24, 550–592. doi:10.1080/10508406.2014.928214
  • Sfard, A. (2007). When the rules of discourse change, but nobody tells you: Making sense of mathematics learning from a commognitive standpoint. Journal of the Learning Sciences, 16, 565–613. doi:10.1080/10508400701525253

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