Nilavra Bhattacharya’s Dissertation

Welcome to the eBook version of Nilavra Bhattacharya’s PhD Dissertation. This website disseminates my PhD research in a format that is more user-friendly and accessible than a 150-page, double-spaced PDF file.

If you are viewing this webpage on a laptop or tablet, you may be able to see the table of contents on the left, and the subheadings for each page on the right. If you are viewing this webpage on your phone, you can navigate between chapters by clicking the three horizontal bars in the top right to view the table of contents. To view a PDF version, click on the cover-sheet below. Happy viewing! 😊

About the author, Nilavra Bhattacharya:

Draft version: 2023-03-31 11:46:56 CST
LongSAL: A Longitudinal Search as Learning Study With University Students


Nilavra Bhattacharya


Presented to the Faculty of the Graduate School
of The University of Texas at Austin
in Partial Fulfillment
of the Requirements
for the Degree of

Doctor of Philosophy

The University of Texas at Austin
August 2023

Click on the coversheet to view a PDF version of this Dissertation.


Learning today is about navigation, discernment, induction, and synthesis of the wide body of information on the Internet present ubiquitously at every student’s fingertips. Learning, or addressing a gap in one’s knowledge, has been well established as an important motivator behind information-seeking activities. The Search as Learning research community advocates that online information search systems should be reconfigured to become educational platforms to foster learning and sensemaking. Modern search systems have yet to adapt to support this function. An important step to foster learning during online search is to identify behavioural patterns that distinguish searchers gaining more vs. less knowledge during search. Previous efforts have primarily studied searchers in the short term, typically during a single lab session. Researchers have expressed concerns over this ephemeral approach, as learning takes place over time, and is not fleeting. In this dissertation, an exploratory longitudinal study was conducted to observe the long-term searching behaviour of students enrolled in a university course, over the span of a semester. Our research aims were to identify if and how students’ searching behaviour changes over time, as they gain new knowledge on a subject; and how do individual traits such as motivation, metacognition, self-regulation, and other individual differences moderate their searching as learning behaviour. We found that differences in these traits do create observable and quantifiable differences in information searching as a learning activity. Students with higher levels of these traits were more effective and efficient in their search behaviours, reported better levels of learning and search outcomes, and obtained better grades. We posit that learning environments should be designed to foster the effective use of metacognitive strategies to help learners develop and apply productive self-regulated learning. Moreover, learning technologies can be used to induce, track, model, and support learners’ metacognition across tasks, domains, and contexts. The study recommends that understanding the complex relationship between motivation and metacognition is essential to designing effective searching as learning environments. Findings from this exploratory longitudinal study will help to build improved search systems that foster human learning and sensemaking, which are more equitable in the face of learner diversity.

সারসংক্ষেপ (Abstract in Bengali)

Bengali version of abstract: TBD. আমার পিএইচডি এডভাইসর পরামর্শ দিয়েছেন যে এই থিসিস এর একটি বাংলা ভাসায় সারসংক্ষেপ ও লিখতে। উনি ওনার থিসিস এর সারসংক্ষেপ ইংরেজি এবং পোলিশ দুই ভাষায় লিখেছিলেন। থিসিসের প্রথম খসড়া জমা দেওয়ার পরে বাংলা সারসংক্ষেপ টি আরও বিস্তারিতভাবে লেখা হবে। বাংলা সংস্করণ এর উৎসর্গ: দিদার জন্য. Bengali version of abstract: TBD.


This section will be fleshed out in more detail after the initial submission. For now, I wish to thank the following people :

PhD Committee Members: Professors

  • Jacek Gwizdka (chair)
  • Soo Young Rieh
  • Matt Lease
  • Rob Capra (UNC Chapel Hill, USA)

Mentors from CHIIR 2021 Doctoral Colloquium: Professors

  • Pertti Vakkari (Tampere Univerisity, Finland)
  • Ian Ruthven (University of Strathclyde, UK)
  • Gerd Berget (Oslo Metropolitan University, Norway)

Nilavra’s Homepage: