Khushboo Thaker

• PhD Student
• PhD at University of Pittsburgh

Massive Open Online Courses (MOOCs) often incorporate lecture-based learning along with lecture notes, textbooks, and videos to students. Moreover, MOOCs also incorporate practice activities and quizzes. Student learning in MOOCs can be tracked and improved using state-of-the-art student modeling. Currently, this means employing conventional studen...

Adaptive textbooks use student interaction data to infer the current state of student knowledge and recommend the most relevant learning materials. A challenge of student modeling for adaptive textbooks is that conventional student models are constructed based on performance data (quiz or problem-solving). However, students' interactions with onlin...

Assessment plays a vital role in learning, as it provides both instructors and students with feedback on the overall effectiveness of their teaching or learning. However, when a student fails to correctly answer certain questions in an assessment (such as a quiz), the student needs specific recommendations that are tailored to their learning needs...

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...

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...

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...

This study represents our preliminary work focused on the health information seeking of caregivers of ovarian cancer (OvCa) patients and survivors. Previous research has predominantly focused on OvCa patients' needs, while neglecting caregivers' needs independently. Through the analysis of social media posts by OvCa caregivers, this study explores...

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...

Developing user personas has been a crucial aspect of human-centered system design for decades as it helps in understanding and segregating users based on their prominent characteristics. However, such a technique has not been applied in developing and improving systems for supporting open government data (OGD) users. Therefore, this paper explores...

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...

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...

Faceted summarization provides briefings of a document from different perspectives. Readers can quickly comprehend the main points of a long document with the help of a structured outline. However, little research has been conducted on this subject, partially due to the lack of large-scale faceted summarization datasets. In this study, we present F...

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...

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.

This paper presents our attempt to create an exploratory search system CovEx for a collection of academic papers related to COVID-19. CovEx uses concept extraction, knowledge graphs, and user-controlled recommendation to assist users with various levels of domain expertise in their information needs. CCS CONCEPTS • Information systems → Graph-based...

The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of adaptive textbooks that can help readers to learn better through adapting to the readers’ learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by internal know...

Academic collections, such as COVID-19 Open Research Dataset (CORD-19), contain a large number of scholarly articles regarding COVID-19 and other related viruses. These articles represent the latest development in combating COVID-19 pandemic in various disciplines. However, it is difficult for laypeople to access these articles due to the term mism...

Over the last 10 years, the world experienced a rapid increase in volume and diversity of digital learning resources. The abundance of digital resources could support a range of powerful educational scenarios, which were not available before. In this paper, we introduce a novel approach that combines fully automatic knowledge modeling, student mode...

This paper presents our attempt to create an exploratory search system CovEx for a collection of academic papers related to COVID-19. CovEx uses concept extraction, knowledge graphs, and user-controlled recommendation to assist users with various levels of domain expertise in their information needs. CCS CONCEPTS • Information systems → Graph-based...

Behnam Rahdari [0000−0001−6514−912X] , Peter Brusilovsky [0000−0002−1902−1464] , Khushboo Thaker [0000−0003−3619−9376] , and Jordan Barria-Pineda [0000−0002−4961−4818] Abstract. In this paper, we introduce an approach that combines automatic domain knowledge modeling, student modeling, and content recommendation approaches to recommend relevant Wik...

With the increased popularity of electronic textbooks, there is a growing interests in developing a new generation of "intelligent textbooks", which have the ability to guide the readers according to their learning goals and current knowledge. The intelligent textbooks extend regular textbooks by integrating machine-manipulatable knowledge such as...

In this work, we described methods used to predict student success on a given programming task and reported our evaluation results.

Existing keyphrase generation studies suffer from the problems of generating duplicate phrases and deficient evaluation based on a fixed number of predicted phrases. We propose a recurrent generative model that generates multiple keyphrases sequentially from a text, with specific modules that promote generation diversity. We further propose two new...

Adaptive textbooks use student interaction data to infer the current state of student knowledge and recommend most relevant learning materials. A challenge of student modeling for adaptive textbooks is that conventional student models are constructed based on performance data (quiz or problem-solving), however, students’ interactions with online te...