Peter Brusilovsky

• PhD
• Professor (Full) at University of Pittsburgh

This chapter offers an introduction to the emerging field of social information access. Social information access focuses on technologies that organize users past interaction with information in order to provide future users with better access to information. These technologies have become increasingly more popular in all areas of information acces...

Springer International Publishing AG, part of Springer Nature 2018. Today, most people find what they are looking for online by using search engines such as Google, Bing, or Baidu. Modern web search engines have evolved from their roots in information retrieval to developing new ways to cope with the unique nature of web search. In this chapter, we...

“Social Navigation” for the Web has been created in response to the problem of disorientation in an information space. It helps users tackle the information overload challenge by visualizing the traces of behavior of other users and adding social affordances to the information space. Despite the popularity of the concept of social navigation, very...

Abstract Over the past decades, computer science educators have developed a multitude of interactive learning resources to support learning in various computer science domains, especially in introductory programming. While such smart content items are known to be beneficial, they are frequently offered through different login-based systems, each wi...

User control and human-AI collaboration are two related directions of research in the modern stream of work on human-centered AI. The field of AI in education was an early pioneer in this area of research, but now it lags behind the work on user control and human-AI collaboration in other areas of AI. This paper attempts to motivate further researc...

Novice programmers can greatly improve their understanding of challenging programming concepts by studying worked examples that demonstrate the implementation of these concepts. Despite the extensive repositories of effective worked examples created by CS education experts, a key challenge remains: identifying the most relevant worked example for a...

Personalized practice systems focus on supporting self-organized learning in a free practice mode. Adapting to the learners’ knowledge and goals, these systems help them navigate the increasing volumes of smart learning content, guide them to practice opportunities that are most appropriate to their level of knowledge and increase their motivation...

Introduction. The underlying assumption of social link-based information access posits that individuals engaging in online social networks derive benefits from the information shared by their online connections. However, this assumption is scrutinized in this study through an examination of the information-sharing behaviours of individual users wit...

The generative large language models (LLMs) are increasingly used for data augmentation tasks, where text samples are paraphrased (or generated anew) and then used for classifier fine-tuning. Existing works on augmentation leverage the few-shot scenarios, where samples are given to LLMs as part of prompts, leading to better augmentations. Yet, the...

Generative artificial intelligence (GenAI) tools, such as large language models (LLMs), generate natural language and other types of content to perform a wide range of tasks. This represents a significant technological advancement that poses opportunities and challenges to educational research and practice. This commentary brings together contribut...

The generative large language models (LLMs) are increasingly being used for data augmentation tasks, where text samples are LLM-paraphrased and then used for classifier fine-tuning. However, a research that would confirm a clear cost-benefit advantage of LLMs over more established augmentation methods is largely missing. To study if (and when) is t...

OvCa patients and caregivers perceived challenges in online health information seeking. The HELPeR recommendation system utilized digital twins to create personas reflecting real-world OvCa patients and caregivers. The aim of this study was to describe the creation of digital twins and demonstrate their use cases in the study. Digital twins of OvCa...

Ovarian cancer (OvCa) patients encounter complex treatment decisions, and often have difficulties in searching and integrating online health information to guide their treatment decision-making. The objective of this study was to explore the preference of online health information among OvCa patients and caregivers, by exploring their preferred con...

Inequities in health information access contribute to disparities in health outcomes. Health recommender systems have emerged as a promising solution to help users find the right information. Despite their various applications, it remains understudied how these systems can aid cancer patients. In this paper, we introduce HELPeR, a recommender syste...

Novice programmers can greatly benefit from using worked examples demonstrating the implementation of programming concepts that are challenging to them. Although large repositories of effective worked examples have been generated by CS education experts, one main challenge is identifying the most relevant worked example in accordance with the parti...

Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This paper investigates why students struggle with integrating component skills–a challenge c...

Explanatory processes are at the core of scientific investigation, legal reasoning, and education. However, effectively explaining complex or large amounts of information, such as that contained in a textbook or library, in an intuitive, user-centered way is still an open challenge. Indeed, different people may search for and request different type...

Objectives Despite the importance of using information for ovarian cancer (OvCa) disease management and decision-making, some women with OvCa do not actively seek out information. The purpose of this study is to investigate factors that influence information seeking behaviors and information avoidance behaviors and information resources among women...

Offline data-driven evaluation is considered a low-cost and more accessible alternative to the online empirical method of assessing the quality of recommender systems. Despite their popularity and effectiveness, most data-driven approaches are unsuitable for evaluating interactive recommender systems. In this paper, we attempt to address this issue...

The 10th edition of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems was held as part of the 17th ACM Conference on Recommender Systems (RecSys), the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. The workshop was organized...

The latest generative large language models (LLMs) have found their application in data augmentation tasks, where small numbers of text samples are LLM-paraphrased and then used to fine-tune downstream models. However, more research is needed to assess how different prompts, seed data selection strategies, filtering methods, or model settings affec...

Automated analysis of programming data using code representation methods offers valuable services for programmers, from code completion to clone detection to bug detection. Recent studies show the effectiveness of Abstract Syntax Trees (AST), pre-trained Transformer-based models, and graph-based embeddings in programming code representation. Howeve...

Prediction of student performance in Introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help st...

Textbooks have evolved over the last several decades in many aspects. Most textbooks can be accessed online, many of them freely. They often come with libraries of supplementary educational resources or online educational services built on top of them. As a result of these enrichments, new research challenges and opportunities emerge that call for...

Self-explanations could increase student’s comprehension in complex domains; however, it works most efficiently with a human tutor who could provide corrections and scaffolding. In this paper, we present our attempt to scale up the use of self-explanations in learning programming by delegating assessment and scaffolding of explanations to an intell...

This paper evaluates an automatically extracted domain model from textbooks and applies learning curve analysis to assess its ability to represent students’ knowledge and learning. Results show that extracted concepts are meaningful knowledge components with varying granularity, depending on textbook authors’ perspectives. The evaluation demonstrat...

The emergence of generative large language models (LLMs) raises the question: what will be its impact on crowdsourcing. Traditionally, crowdsourcing has been used for acquiring solutions to a wide variety of human-intelligence tasks, including ones involving text generation, manipulation or evaluation. For some of these tasks, models like ChatGPT c...

The ability to automatically assess learners' activities is the key to user modeling and personalization in adaptive educational systems.The work presented in this paper opens an opportunity to expand the scope of automated assessment from traditional programming problems to code comprehension tasks where students are requested to explain the criti...

To recognize the current and future trends and challenges in computer science education educational materials for the next decade, the authors of this work provide a conversation to voice the computer science community's experience and expertise on these trends. One of the biggest challenges for introductory computing courses in the next few years...

The emergence of generative large language models (LLMs) raises the question: what will be its impact on crowdsourcing? Traditionally,crowdsourcing has been used for acquiring so-lutions to a wide variety of human-intelligence tasks, including ones involving text generation,modification or evaluation. For some of these tasks, models like ChatGPT ca...

Background Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives Th...

False information detection models are susceptible to adversarial attacks. Such susceptibility is a critical weakness of detection models. Automated creation of adversarial samples can ultimately help to augment training sets and create more robust detection models. However, automatically generated adversarial samples often do not preserve the info...

Knowledge Tracing (KT), which aims to model student knowledge level and predict their performance, is one of the most important applications of user modeling. Modern KT approaches model and maintain an up-to-date state of student knowledge over a set of course concepts according to students' historical performance in attempting the problems. Howeve...

Carousel-based recommendation interfaces allow users to explore recommended items in a structured, efficient, and visually-appealing way. This made them a de-facto standard approach to recommending items to end users in many real-life recommenders. In this work, we try to explain the efficiency of carousel recommenders using a carousel click model,...

Studies of technology-enhanced learning (TEL) environments indicated that learner behavior could be affected (positively or negatively) by presenting information about their peer groups, such as peer in-system performance or course grades. Researchers explained these findings by the social comparison theory, competition, or by categorizing them as...

The advancement of computational Artificial Intelligence (AI) in the recent decade has been transformative for many domains, including AI in Education. One direction, where it has caused a noticeable increase in research activity, is application of AI technologies to enhance digital textbooks by making them more interactive, engaging, adaptive, and...

One of the main directions of increasing the educational value of a digital textbook is its enrichment with interactive content. Such content can come from outside the textbooks - from multiple existing repositories of educational resources. However, finding the right place for such external resources is not always a trivial task. There exist multi...

One of the main directions of increasing the educational value of a digital textbook is its enrichment with interactive content. Such content can come from outside the textbooks - from multiple existing repositories of educational resources. However, finding the right place for such external resources is not always a trivial task. There exist multi...

Program code analysis is an important component in several kinds of intelligent educational systems for CS education. The ability to analyze and understand student-written code enables these systems to assess students learning and understanding of the essential programming constructs. The central issue of code analysis is a concise code representat...

Methods to encode high-dimensional features into dense vectors or "embeddings" have gained attention in educational data mining to transform large state data spaces into condensed representations suitable as input to machine learning algorithms. One such technique is Code2Vec, an embedding technique developed by software engineers to predict method...

False information detection models are susceptible to adversarial attacks. Such susceptibility is a critical weakness of detection models. Automated creation of adversarial samples can ultimately help to augment training sets and create more robust detection models. However, automatically generated adversarial samples often do not preserve the info...

Adaptive information access systems is one of the most popular types of adaptive systems. It includes adaptive search, recommender system, adaptive navigation support, and adaptive information visualization. This is also one of the oldest types of adaptive systems where the ideas of user control were explored. Motivated by a timely selection of use...

The transition of textbooks from printed copies to digital and online formats has facilitated numerous attempts to enrich them with various kinds of interactive functionalities, link them with external resources or extract valuable information from them. As a result, new research challenges and opportunities emerge that call for the application of...

Carousel-based interfaces with multiple topic-focused item lists have emerged as a de-facto standard for presenting recommendation results to end-users in real-life recommender systems. In this paper, we attempt to formalize and explain the “magic” power of carousel-based interfaces from a traditional hypertext prospect of navigability. By applying...

We present here a novel instructional resource, called DeepCode, to support deep code comprehension and learning in intro-to-programming courses (CS1 and CS2). DeepCode is a set of instructional code examples which we call a codeset and which was annotated by our team with comments (e.g., explaining the logical steps of the underlying problem being...

Background Patients and caregivers widely use online health communities (OHCs) to acquire knowledge from peers. Questions posed in OHCs reflect participants’ learning objectives and differ in their level of cognitive complexity. However, little is known about the topics and levels of participants’ learning objectives and the corresponding support t...

BACKGROUND Patients and caregivers have been widely using Online Health Communities (OHCs) to acquire knowledge from peers. Questions posed in OHCs reflect the participant's learning objectives and are known to differ in the level of cognitive complexity. However, little is known about the topics and levels of participant learning objectives and th...

An interactive recommender system pursues two somewhat contradictory goals. On one hand, the system should provide highly relevant recommendations with the best match to the overall user needs. On the other hand, the recommendations should be sufficiently diverse to cover a range of users' possible interests. Such recommendations increase chances t...

Educational data mining research has demonstrated that the large volume of learning data collected by modern e-learning systems could be used to recognize student behavior patterns and group students into cohorts with similar behavior. However, few attempts have been done to connect and compare behavioral patterns with known dimensions of individua...

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at...

We present in this paper a summary analysis of log files collected during an experiment designed to test the hypothesis that prompting for free self-explanations leads to better comprehension of computer code examples. Indeed, the results indicate that students who were prompted to self-explain while trying to understand code examples performed sig...

The overarching goal of our project is to develop a recommender system that personalize online health-related materials to patients and their caregivers based on their needs and knowledge level. • The recommender system will address the knowledge discrepancy between patients and online health information, and accurately estimate the required knowle...

Ovarian cancer (OvCa) patients and caregivers have constant and evolving information needs. To meet their needs, they seek information from various resources, including online health information. Although about 60% of cancer patients are now using the Internet to meet their information needs, little is known about online health information seeking...

Using carousels to present recommendation results has been widely adapted for consumer-focused applications such as recommending movies and music. Carousel-based interfaces engage users in the recommendation process, leaving it to the user to decide which category of items is most relevant to them, yet leaving it to AI to produce a ranking of both...

BACKGROUND Online health communities (OHCs) provide ovarian cancer (OvCa) patients, survivors, and their caregivers assistance beyond their traditional support channels. OvCa OHC promotes connection and exchange information among users who had similar experiences. This exchange of information often leads to resource sharing amongst users, as web li...

Background Online health communities (OHCs) provide patients and survivors of ovarian cancer (OvCa) and their caregivers with help beyond traditional support channels, such as health care providers and clinicians. OvCa OHCs promote connections and exchanges of information among users with similar experiences. Users often exchange information, which...

With the increased popularity of electronic textbooks, there is a growing interest in developing a new generation of “intelligent textbooks,” which have the ability to guide readers according to their learning goals and current knowledge. Intelligent textbooks extend regular textbooks by integrating machine-manipulable knowledge, and the most popul...

In recent years, researchers in the field of recommender systems have explored a range of advanced interfaces to improve user interactions with recommender systems. Some of the major research ideas explored in this new area include the explainability and controllability of recommendations. Controllability enables end users to participate in the rec...

This paper contributes to the research on explainable educational recommendations by investigating explainable recommendations in the context of personalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explai...

This paper presents our attempt to create an exploratory search system, PaperExplorer, for a historic archive of conference proceedings. PaperExplorer uses concept extraction, knowledge graphs, and user-controlled recommendation to assist users with various levels of domain expertise in their information needs.

Over the last 10 years, learning analytics have provided educators with both dashboards and tools to understand student behaviors within specific technological environments. However, there is a lack of work to support educators in making data-informed design decisions when designing a blended course and planning appropriate learning activities. In...

With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different e-learni...

Abstract Research has demonstrated that people generally think both their knowledge and performance levels are greater than they are. Although several studies have suggested that knowledge and progress visualization offered by open learner modeling (OLM) technology might influence students’ self-awareness in a positive way, insufficient evidence ex...

Purpose Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system. Design/methodology/approach This case study was conducted with 40 undergradu...

Ovarian cancer (OvCa) can be a deadly gynecological cancer affecting about 22k women per year in the United States with a significant recurrence rate [1]. Women with OvCa and their caregivers often seek support from online health communities (OHCs) [2]. These OHCs allow for the exchange of information and resources with other individuals who have h...

Finding research advisors is an important and challenging task for college students. On one hand, a research advisor that matches student interests and past preparation could fully engage the student with an exciting and productive research experience. On the other hand, students are frequently unable to formulate their interests and experience in...

Meeting other scholars at conferences is often a stochastic, intuition-driven process. Social recommender systems can support identifying new collaboration partners that one might not naturally choose. However, to boost the accumulation of social capital, such systems must be designed for diversifying social connections. This paper draws from the e...

In this paper, we introduce an approach that combines automatic domain knowledge modeling, student modeling, and content recommendation approaches to recommend relevant Wikipedia articles for students working with online electronic textbooks.