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Presentation Notice

by Halle Smith -

Representing the AdultEd research team, Dr. John Sabatini and John Hollander presented their research at the 32nd Annual Meeting of the Society for Text and Discourse.

One presentation was titled “Foundational reading skills and learner characteristics in an adult literacy intervention.” In this presentation, they surveyed how adult literacy learners are characterized by their diversity, in terms of both educational histories and cognitive skillsets. In their research, they examined difference score data from a component reading skills assessment battery bookending an adult literacy intervention including an adult literacy-focused intelligent tutoring system. By clustering learners based on their performance characteristics during intervention, researchers were able to observe whether gains were made in foundational reading skills, revealing for whom this intervention might be most (or least) effective. 


The other presentation was titled, “How Lexical Properties of Test Items Impact Adolescent and Adult Learner Text Processing.” The purpose of this study was to examine what lexical properties of foundational skills test items reveal about text processing in adolescents and adults. In the US, significant proportions of both populations failed to achieve comprehension proficiency sufficient to succeed in higher education contexts. In this study, the researchers took a deep dive into the surface code linguistic knowledge and processing of adolescents and adults who have struggled to achieve reading comprehension proficiency.


 Hollander, J., Sabatini, J., Graesser, A., Greenberg, D., O’Reilly, T., & Frijters, J. (July, 2022). Foundational reading skills and learner characteristics in an adult literacy intervention. Presented at the 32nd Annual Meeting of the Society for Text and Discourse. 

Sabatini, J., Hollander, J., Graesser, A., & O’Reilly, T., (2022, July). How Lexical Properties of Test Items Impact Adolescent and Adult Learner Text Processing. Presented at the 32nd Annual Meeting of the Society for Text and Discourse.

Publication Notice

by Halle Smith -

Representing the AdultEd research team, Dr. John Sabatini and John Hollander presented their research at the 23rd International Conference on Artificial Intelligence in Education in July 2022.

There, Sabatini, John Hollander, and Dr. Graesser presented “How item and learner characteristics matter in intelligent tutoring systems data.” Using items from AutoTutor for Adult Reading Comprehension (AutoTutor-ARC), the researchers explored a method for categorizing items as instructive, evaluative, motivational, or potentially flawed. At the same time, the researchers evaluated how assessing learner component reading skills can inform various aspects of learner needs. To do this, they compared learners who were classified as proficient, underengaged, conscientious, or struggling readers based on their experiences with AutoTutor. Together, these foci suggested the utility of integrating assessments with instruction.

Hollander, J., Sabatini, J., Graesser, A. (2022, July). How item and learner characteristics matter in intelligent tutoring systems data. In Lecture Notes in Artificial Intelligence: Proceedings of the 23rd International Conference on Artificial Intelligence in Education

AutoTutor-ARC Joins CREATE Network

by Halle Smith -
AutoTutor for Adult Reading Comprehension (AutoTutor-ARC) has been accepted as a part of a national initiative called the CREATE Network. Funded by the IES and led by the American Institutes for Research (AIR), the CREATE network strives to support teaching and learning by researching technology-enabled instruction. With CREATE, AutoTutor-ARC prioritizes research making technology-enabled instruction accessible to adult education instructors and students.


Also in the CREATE network are projects from WestEd, University of Massachusetts Amherst, University of Minnesota-Duluth, AIR, EdTech Center @ World Education, and Georgia State University.


The CREATE Network’s webpage can be found at this link.

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