Ram B. Basnet

Towards examining learner behaviors in a medical intelligent tutoring system: A Hidden Markov Model approach

In BioWorld, a medical intelligent tutoring system, novice physicians are tasked with diagnosing virtual patient cases. Although we are often interested in considering whether learners diagnosed the case correctly or not, we cannot discount the actions that learners take to arrive at a final diagnosis. Thus, the consideration of the sequence of actions becomes important. In this preliminary study, we propose a line of research to investigate learner actions involved in diagnosing virtual patient cases using Hidden Markov Models.

Augmenting the novice-expert overlay model in an intelligent tutoring system: Using confidence-weighted linear classifiers

In BioWorld, a medical intelligent tutoring system, novice physicians are tasked with solving virtual patient cases. Whilst the importance of modeling and predicting clinical reasoning is recognized, an important aspect of the learner contribution remains unexplored - the written case summary prepared by the learner. The premise of investigating the case summaries is that it captures the thought and process of the learners in solving the cases; since, the case summaries hold important reasoning information, it makes sense to incorporate it as part of the novice-expert overlay model. In this paper, case summaries written by novices and experts were considered as an addendum to the existing novice-expert overlay model in the BioWorld system. Toward this goal, using a promising new classification method called confidence-weighted linear classifiers, this paper proposes a way to augment the novice-expert overlay model in BioWorld.

Exploring Computer Science Students' Continuance Intentions to Use Kattis.

Teaching programming concepts to enhance students’ problem solving and computational thinking skills is a challenging task, especially when students enter college with little to no preparation, or they lack the interest or capacity for programming. Online platforms that serve as automated practice and assessment systems have been offered as potential tools for supporting programming skills development, providing feedback, and motivating students. The present article discusses the use of an online automated practice and assessment system called Kattis for homework assignments and final project in three computer science courses. The goal of the present study was to ascertain students’ continuance intentions to use Kattis. We attempt to address this by using partial least squares on data from a survey of 50 students. The findings of the present study suggest that continuance intentions to use Kattis is driven by students’ level of satisfaction with the system, the degree of students’ confirmation of expectations, and the perceived usefulness of the system.

Social network analysis of twitter use during the AERA 2017 annual conference

Social network analysis can provide insight into the educational research community as it manifests and evolves online. This study presents a social network analysis of Twitter use during the American Educational Research Association 2017 Annual Conference. The overall social network is sparse with low density, with a few very active nodes and many unconnected Twitter users. Tweets were positive or neutral and rarely negative. Degree of centrality and of closeness of the top 10 users is high, relative to the top 100 users as centrality, closeness, and betweenness taper off quickly. We interpret this as due to the large number of non-intersecting special interest groups that dilute the overall density of the network. Future social network analysis studies should compare SIGs on various metrics and track their developments over time.