In this talk, I will firstly outline a framework connecting outcomes (learning or eventual performance on assessment tasks) with input variables such as persons’ skills and tasks’ demands through task engagement process variables. This framework suggests that task engagement processes mediate effects of person and task variables on task performance. Most importantly, the association of task variables and task engagement is moderated by person variables, and the association of person variables with task engagement is moderated by task variables. Also, task engagement predicts task performance conditionally on both person and task variables. Secondly, I elaborate how especially 
the interaction terms included in this model can help to conceptually disambiguate otherwise ambiguous process measures, like time-on-task, which can be indicative of both cognitive (in-) efficiency and scrutiny or engagement, or page visits in hypertext reading, which might be indicative of either curiosity or disorientation. All analyses presented will use reading digital text and the related domain of complex problem solving as examples. 

Related literature 

• Eichmann, B., Goldhammer, F., Greiff, S., Brandhuber, L., & Naumann, J. (in press). Using process data 
  to explain group differences in complex problem solving. Journal of Educational Psychology. 
  https://dx.doi.org/10.1037/edu0000446
• Naumann, J. (2019). The skilled, the knowledgeable, and the motivated: Investigating the strategic 
  allocation of time on task in a computer-based assessment. Frontiers in Psychology, 10, 1429. 
  https://dx.doi.org/10.3389/fpsyg.2019.01429
• Hahnel, C., Goldhammer, F., Kröhne, U., & Naumann, J. (2017). Reading digital text involves working 
  memory updating based on task characteristics and reader behavior. Learning and Individual 
  Differences, 59, 149-157. https://doi.org/10.1016/j.lindif.2017.09.001
• Naumann, J. & Goldhammer, F. (2017). Time-on-task effects in digital reading are non-linear and 
  moderated by persons' skills and tasks' demands. Learning and Individual Differences, 53, 1-16. 
  https://doi.org/10.1016/j.lindif.2016.10.002
• Naumann, J. & Salmerón. L. (2016). Does navigation always predict performance? Effects of navigation on digital reading are moderated by comprehension skills. The International Review of Research in Open and Distributed Learning, 17(1), 42-59. https://dx.doi.org/10.19173/irrodl.v17i1.2113
• Goldhammer, F., Naumann, J. & Greiff, S. (2015). More is not always better: The relation between item responses and item response times in Raven's matrices. Journal of Intelligence, 3, 21-40.
  https://dx.doi.org/10.3390/jintelligence3010021 
• Naumann, J. (2015). A model of online reading engagement: Linking engagement, navigation, and performance in digital reading. Computers in Human Behavior, 53, 263-277.
  https://doi.org/10.1016/j.chb.2015.06.051
• Goldhammer, F., Naumann, J., Stelter, A., Rölke, H., Tóth, K., & Klieme, E. (2014). The time-on-task effect in reading and problem solving is moderated by item difficulty and ability: Insights from computer-based large-scale assessment. Journal of Educational Psychology, 106, 608-626.
  https://doi.org/10.1037/a0034716
• Naumann, J., Goldhammer, F., Rölke, H. & Stelter, A. (2014). Erfolgreiches Problemlösen in technologiebasierten Umgebungen: Wechselwirkungen zwischen Interaktionsschritten und Aufgabenanforderungen. Zeitschrift für Pädagogische Psychologie, 28, 193-203.
  https://doi.org/10.1024/1010-0652/a000134