Sebastian de la Chica

Computational foundations for personalizing instruction with digital libraries

This paper describes our progress towards automating adaptive personalized instruction based on student conceptual understandings using digital libraries. The reported approach merges conversational learning theory with advances in natural language processing to enable personalized pedagogical interactions. Multi-document summarization techniques serve as the computational basis to process digital library resources and automatically construct a rich domain model on earthquakes and plate tectonics for high school age learners. Shallow semantic analysis and graph-based techniques are used to computationally diagnose student understandings that enable conceptual personalizations integrating digital library resources. The evaluation of the implemented algorithms indicates that digital libraries may serve as knowledge platforms to support the automated construction of rich domain models and the diagnosis of student conceptual understandings. Furthermore, this approach introduces a novel and effective alternative to prior work in adaptive learning environments in terms of scalability and portability, thus tackling important challenges associated with supporting personalized instruction using digital libraries.

Towards automatic conceptual personalization tools

This paper describes the results of a study designed to validate the use of domain competency models to diagnose student scientific misconceptions and to generate personalized instruction plans using digital libraries. Digital library resources provided the content base for human experts to construct a domain competency model for earthquakes and plate tectonics encoded as a knowledge map. The experts then assessed student essays using comparisons against the constructed domain competency model and prepared personalized instruction plans using the competency model and digital library resources. The results from this study indicate that domain competency models generated from select digital library resources may provide the desired degree of content coverage to support both automated diagnosis and personalized instruction in the context of nationally-recognized science learning goals. These findings serve to inform the design of personalized instruction tools for digital libraries.

Pedagogically Useful Extractive Summaries for Science Education

This paper describes the design and evaluation of an extractive summarizer for educational science content called COGENT. COGENT extends MEAD based on strategies elicited from an empirical study with science domain and instructional design experts. COGENT identifies sentences containing pedagogically relevant concepts for a specific science domain. The algorithms pursue a hybrid approach integrating both domain independent bottom-up sentence scoring features and domain-aware top-down features. Evaluation results indicate that COGENT outperforms existing summarizers and generates summaries that closely resemble those generated by human experts. COGENT concept inventories appear to also support the computational identification of student misconceptions about earthquakes and plate tectonics.

A personalized learning environment

We report on the current research activities and results obtained through the Concept Learning service for Concept Knowledge (CLICK) and present a demonstration of the system. This poster session will focus on a demonstration of the CLICK system and the results of the learning study

Extractive Summaries for Educational Science Content

This paper describes an extractive summarizer for educational science content called COGENT. COGENT extends MEAD based on strategies elicited from an empirical study with domain and instructional experts. COGENT implements a hybrid approach integrating both domain independent sentence scoring features and domain-aware features. Initial evaluation results indicate that COGENT outperforms existing summarizers and generates summaries that closely resemble those generated by human experts.

SciNews online: scaffolding the construction of scientific explanations

Middle and high-school science teachers have traditionally introduced current events in the classroom to leverage news topics relevant to the curriculum, such as the Sumatra Tsunami or Hurricane Katrina. SciNews Online is an online research environment co-designed with science teachers for learners to construct web reports on the science behind the news on natural disasters. Writing scientific explanations provides valuable learning opportunities for learners to engage in a realistic and educationally relevant science task. Here I highlight the design of the Scientific Explanation Activity, a scaffolded environment that supports learners. construction of scientific explanations using multiple online sources. The Scientific Explanation Activity focuses on supporting the development of key information literacy skills for sense-making in science inquiry, namely information integration across sources and effective scientific argumentation.