Chutima Boonthum

iSTART: interactive strategy training for active reading and thinking.

Interactive Strategy Training for Active Reading and Thinking (iSTART) is a Web-based application that provides young adolescent to college-age students with high-level reading strategy training to improve comprehension of science texts. iSTART is modeled after an effective, human-delivered intervention called self-explanation reading training (SERT), which trains readers to use active reading strategies to self-explain difficult texts more effectively. To make the training more widely available, the Web-based trainer has been developed. Transforming the training from a human-delivered application to a computer-based one has resulted in a highly interactive trainer that adapts its methods to the performance of the students. The iSTART trainer introduces the strategies in a simulated classroom setting with interaction between three animated characters—an instructor character and two student characters— and the human trainee. Thereafter, the trainee identifies the strategies in the explanations of a student character who is guided by an instructor character. Finally, the trainee practices self-explanation under the guidance of an instructor character. We describe this system and discuss how appropriate feedback is generated.

Assessing the format of the presentation of text in developing a Reading Strategy Assessment Tool (R-SAT)

We are constructing a new computerized test of reading comprehension called the Reading Strategy Assessment Tool (R-SAT). R-SAT elicits and analyzes verbal protocols that readers generate in response to questions as they read texts. We examined whether the amount of information available to the reader when reading and answering questions influenced the extent to which R-SAT accounts for comprehension. We found that R-SAT was most predictive of comprehension when the readers did not have access to the text as they answered questions.

iSTART: paraphrase recognition

Paraphrase recognition is used in a number of applications such as tutoring systems, question answering systems, and information retrieval systems. The context of our research is the iSTART reading strategy trainer for science texts, which needs to understand and recognize the trainees input and respond appropriately. This paper describes the motivation for paraphrase recognition and develops a definition of the strategy as well as a recognition model for paraphrasing. Lastly, we discuss our preliminary implementation and research plan.

iSTART 2: Improvements for efficiency and effectiveness

AbstractiSTART (interactive strategy training for active reading and thinking) is a Web-based reading strategy trainer that develops students’ ability to self-explain difficult text as a means to improving reading comprehension. Its curriculum consists of modules presented interactively by pedagogical agents: an introduction to the basics of using reading strategies in the context of self-explanation, a demonstration of self-explanation, and a practice module in which the trainee generates self-explanations with feedback on the quality of reading strategies contained in the self-explanations. We discuss the objectives that guided the development of the second version of iSTART toward the goals of increased efficiency for the experimenters and effectiveness in the training. The more pedagogically challenging high school audience is accommodated by (1) a new introduction that increases interactivity, (2) a new demonstration with more and better focused scaffolding, and (3) a new practice module that provides improved feedback and includes a less intense but more extended regimen. Version 2 also benefits experimenters, who can set up and evaluate experiments with less time and effort, because pre- and posttesting has been fully computerized and the process of preparing a text for the practice module has been reduced from more than 1 person-week to about an hour’s time.

Evaluating Self-Explanations in iSTART: Word Matching, Latent Semantic Analysis, and Topic Models

iSTART (Interactive Strategy Trainer for Active Reading and Thinking) is a webbased, automated tutor designed to help students become better readers via multimedia technologies. It provides young adolescent to college-aged students with a program of self-explanation and reading strategy training [19] called Self-Explanation Reading Training, or SERT [17], [21], [24], [25]. The reading strategies include (a) comprehension monitoring, being aware of one’s understanding of the text; (b) paraphrasing, or restating the text in different words; (c) elaboration, using prior knowledge or experiences to understand the text (i.e., domain-specific knowledge-based inferences) or common sense, using logic to understand the text (i.e., domain-general knowledge based inferences); (d) predictions, predicting what the text will say next; and (e) bridging, understanding the relation between separate sentences of the text. The overall process is called “self-explanation” because the reader is encouraged to explain difficult text to him- or herself. iSTART consists of three modules: Introduction, Demonstration, and Practice. In the last module, students practice using reading strategies by typing self-explanations of sentences. The system evaluates each self-explanation and then provides appropriate feedback to the student. If the explanation is irrelevant or too short, the student is required to add more information. Otherwise, the feedback is based on the level of overall quality.

Introducing an experimental cognitive robotics curriculum at historically black colleges and universities

A successful collaboration between Spelman College and Carnegie Mellon University led to an NSF-funded Broadening Participation in Computing project to set up robotics education laboratories and introduce undergraduate instruction in cognitive robotics at three other Historically Black Colleges and Universities (HBCUs). We give a brief overview of cognitive robotics and the Tekkotsu software architecture, and describe our experiences teaching computer science students with no previous robotics exposure to program sophisticated mobile robots.

Preposition senses: generalized disambiguation model

Our previous study on disambiguating the preposition “with” (using WordNet for hypernym and meronym relations, LCS for verb and preposition lexical information, and features of head and complement) looked promising enough to warrant study for other prepositions. Through investigation of ten frequently used prepositions, this paper describes general senses of prepositions and sense-case definitions, introduces a novel generalized sense disambiguation model, and demonstrates how this benefits a paraphrase recognition system.

Mobile computing: Opportunities for optimization research

The last 20 years have seen a tremendous growth in mobile computing and wireless communications and services. Most of the research in mobile computing has addressed the fundamental engineering issues involved in building and exploiting mobile and wireless systems, ranging from cellular, to satellite, to ad hoc and, more recently, to sensor networks. On the other hand, optimization research in mobile computing and wireless communications has received, in relative terms, less attention and was related mostly to optimizing the performance of individual communication protocols. Supporting mobility in all its aspects from cellular services to multimedia brings to the fore new problems and opportunities for optimization research. This paper is a survey of some of the promising areas in which optimization can be used to solve mobile computing problems.