This thesis focuses on learning natural language interfaces using synchronous grammars, λ-calculus and statistical modeling of parse probabilities. A major focus of the thesis has been to replicate Mooney and Wong’s λ-WASP [17] algorithm and implement it inside the C-PHRASE [12] Natural Language Interface (NLI) system. By doing this we can use C-PHRASE’s more expressive and transportable meanin...

Uplift modeling is a classification method that determines the incremental impact of an action on a given population. Uplift modeling aims at maximizing the area under the uplift curve, which is the difference between the subject and control sets’ area under the lift curve. Lift and uplift curves are seldom used outside of the marketing domain, whereas the related ROC curve is frequently used i...

The concept of “incarnational ministry,” which is often taught in cross-cultural ministry or missions training, offers practical value to academic liaison librarianship, namely: getting out the library and going where users are, being a life-long learner, modeling humility during interactions with patrons.

The development of Intelligent Tutoring Systems (ITS) and eLearning systems has been progressing largely independently over the past several years. Both types of systems have strengths and weaknesses – ITSs are typically domain specific and rely on concise knowledge modeling and learner modeling, while eLearning systems are deployable in a wide range of circumstances and focus on connecting lea...

This study discusses student’s experiences on Web-based learning in a Helsinki Virtual Open University HEVI [01] environment with the help of a new modeling technique, Bayesian networks. The advantage of Bayesian network models relies both on improved modeling capabilities and in the possibility to use such models to implement new integrative modules that enable interactive activities (e.g. tes...

Modeling learners’ emotional states is a promising tool for enhancing learning outcomes and tutoring abilities. In this paper, we present a new perspective of learner emotional modeling according to two fundamental dimensions, namely mental workload and engagement. We hypothesize that analyzing results from learners’ workload and engagement evolution can help Intelligent Tutoring Systems diagno...

We propose a sequence labeling framework with a secondary training objective, learning to predict surrounding words for every word in the dataset. This language modeling objective incentivises the system to learn general-purpose patterns of semantic and syntactic composition, which are also useful for improving accuracy on different sequence labeling tasks. The architecture was evaluated on a r...

Learning progressions (LPs) are a recent educational theory pertaining to student modeling. LPs argue that students with equal test scores may nonetheless have different conceptualizations of the material, with varying degrees of maturity. However, there is little empirical validation for LPs. To this end, we mapped two physics LPs (one predefined, one described in the paper) onto the answer ch...

This paper introduces a set of resources that provide web learning environments with student modeling services. SAMUEL is a user modeling server for registering, updating and maintaining student knowledge data from different sources that use their own ontologies. In order to make inferences about student knowledge, it becomes necessary to establish equivalences between concepts of different dom...

This position paper discusses the need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems. We outline several open issues related to adaptive learning content delivery and present an approach to deal with these issues based on the integration of two existing systems AIMS (taskbased information retrieval environment) and STyLE-OLM ...