Nadia A Najjar

University of North Carolina at Charlotte | UNC Charlotte · Department of Software & Information Systems

The COVID-19 pandemic led the majority of educational institutions to rapidly shift to primarily conducting courses through online, remote delivery. Across different institutions, the tools used for synchronous online course delivery varied. They included traditional video conferencing tools like Zoom, Google Meet, and WebEx as well as non-traditio...

Diet diversification can facilitate both positive health outcomes and greater enjoyment in food consumption. Case-based recommendation can play an important role to promote a more diverse diet by connecting users with more diverse options in meal planning. Our research investigates conversational CBR approaches to support greater diversity in recom...

Making recommendations to groups of users gives rise to significant challenges for group modeling and recommenda-tion, but also particularly for evaluating group recommender systems. A common approach for scalability in group rec-ommender research is to generate synthetic groups from tra-ditional single-user datasets, and we focus on this context....

Understanding computing concepts is one of the foundational elements of computational thinking, which helps students formulate logic and algorithms for effectively developing and designing codes. However, novice learners often struggle to understand basic computing concepts, such as variables, loops, arrays, conditionals, and functions. This is oft...

Innovative approaches to personalized and adaptive learning are being developed that leverage advances in AI and access to large datasets. In this paper, we focus on computational models of novelty in large datasets of documents with the goal to encourage curiosity in student learning. While encouraging curiosity is important in all learning experi...

Diet diversification has been shown both to improve nutritional health outcomes and to promote greater enjoyment in food consumption. CBR has a rich history in direct recommendation of recipes and meal planning, as well as conversational exploration of the possibilities for new food items. But more limited attention has been given to incorporating...

Conversational recommender systems help to guide users in exploring the search space in order to discover items of interest. During the exploration process, the user provides feedback on recommended items to refine subsequent recommendations. Critiquing as a way of feedback has proven effective for conversational interactions. In addition, diversif...

This paper describes Pique, a web-based recommendation system that applies word embedding and a sequence generator to present students with a sequence of scientific paper recommendations personalized to their background and interest. The use of natural language processing (NLP) on learning materials enables educational environments to present stude...

The Personalised Curiosity Engine (PQE, pronounced “pique”) is a framework for computational design systems that models the curiosity of an individual user. This model is then used to synthesise designs that stimulate that user’s curiosity. PQE extends our previous research in modelling surprise and curiosity by adding a model of a specific user to...

This paper presents a dual-cycle CBR model in the domain of recipe generation. The model combines the strengths of deep learning and similarity-based retrieval to generate recipes that are novel and valuable (i.e. they are creative). The first cycle generates abstract descriptions which we call “design concepts” by synthesizing expectations from th...

Case-Based Reasoning has been studied as a methodology to support ratings-based collaborative recommendation, but this predom-inantly targets the context of an individual end-user. There are, how-ever, many circumstances where several people participating together in a group activity could benefit from recommendations tailored to the group as a who...

As recommender systems have become commonplace to support individual decision making, a need has also been recognized for systems that tailor and provide recommendations to a group of users together rather than individuals alone. Group recommender research to date has focused on evaluating strategies for aggre-gating profiles of group members to fo...

Group recommendation presents significant challenges in evolving best practice approaches to group modeling, but even moreso in dataset collection for testing and in developing principled evaluation approaches across groups of users. Early research provided more limited, illustrative evaluations for group recommender approaches, but recent work has...

Public school choice at the primary and secondary levels is a key element of the U.S. No Child Left Behind Act of 2001 (NCLB). If a school does not meet assessment goals for two consecutive years, by law the district must offer students the opportunity to transfer to a school that is meeting its goals. Making a choice with such potential impact on...

Geovisualization has traditionally played a critical role in analysis and decision-making, but recent developments have also brought a revolution in widespread online access to geographic data and integration tools, particularly for map-based interfaces. This next generation of geovisualization applications is often characterized by high interactiv...

Public school choice at the primary and secondary levels is one of the key elements of the U.S. No Child Left Behind Act of 2001 (NCLB). If a school does not meet assessment goals for two consecutive years, by law the district must offer students the opportunity to transfer to a school that is meeting its goals. Making a choice with such potential...