Assessing computer literacy of adults with low literacy skills
Adaptive learning technologies hold great promise for improving the reading skills of adults with low literacy, but adults with low literacy skills typically have low computer literacy skills. In order to determine whether adults with low literacy skills would be able to use an intelligent tutoring system for reading comprehension, we adapted a 44 task computer literacy assessment and delivered it to 114 adults with reading skills between 3rd and 8th grade levels. This paper presents four analyses on these data. First, we report the pass/fail data natively exported by the assessment for particular computer-based tasks. Second, we undertook a GOMS analysis of each computer-based task, to predict the task completion time for a skilled user, and found that it negatively correlated with proportion correct for each item, r(42) = −.4, p = .01. Third, we used the GOMS task decomposition to develop a Q-matrix of component computer skills for each task, and using logistic mixed effects models on this matrix identified five component skills highly predictive of the success or failure of an individual on a computer task: function keys, typing, using icons, right clicking, and mouse dragging. And finally, we assessed the predictive value of all component skills using logistic lasso.
Proceedings of the 10th International Conference on Educational Data Mining, EDM 2017
Olney, A., Bakhtiari, D., Greenberg, D., & Graesser, A. (2017). Assessing computer literacy of adults with low literacy skills. Proceedings of the 10th International Conference on Educational Data Mining, EDM 2017, 128-134. Retrieved from https://digitalcommons.memphis.edu/facpubs/7416