IISER Pune Digital Repository

A repository of scholarly research output from the Indian Institute of Science Education and Research (IISER) Pune.

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Theses submitted to IISER Pune in partial fulfilment of the requirements of the BS-MS dual degree, MSc. and Ph.D programmes. Also, project reports submitted by the students.

Recent Submissions

Access status: Embargo ,
English Language Acquisition and Beyond: Evaluating the Impact of Stories in an Urdu-medium Classroom in India
(2026-10) SHAIKH, MARYAM KALEEM; SANCHETI, POOJA; Dept. of Humanities and Social Sciences; 20213503
This thesis investigates the effectiveness of reading stories, mediated through a multilingual dialogic pedagogy, in fostering English language acquisition among Urdu-medium students. Urdu-medium schools in India, often overlooked in terms of infrastructure and resources, face persistent challenges of high drop-out rates and low academic achievement, especially in English language proficiency. Despite these challenges, Urdu-medium schools remain under-resourced and under-researched. Addressing this gap, this study introduces a teaching intervention modelled on key theories of Second Language Acquisition, such as Krashen’s Input Hypothesis (1982), Swain’s Output Hypothesis (2005), and the concept of reading for pleasure, in tandem with dialogic and critical pedagogies situated within the framework of multilinguality (Agnihotri, 2014). The intervention, implemented with Standard 8 students at an Urdu-medium school in Pune, India, examines the impact of a story-based pedagogy on both linguistic and extra-linguistic skills, particularly those of motivation, learner autonomy, and critical thinking. The study adopts a mixed-methods framework, involving a quasi-experimental design, complemented by semi-structured interviews with students, teachers and parents; survey questionnaires; classroom observations; and case studies. Findings reveal significant improvement in students’ language skills, such as in reading comprehension, writing fluency, and vocabulary. Qualitative insights further reveal students’ evolving desire for and exercise in learner agency and critical reflection. These observations highlight how dialogic engagement with stories encouraged students to read, reflect, collaborate, and engage in meaning-making processes, while maintaining an anxiety-free environment. This thesis demonstrates the transformative potential of a story-based, multilingual, and dialogic pedagogy in low-resource educational contexts. It argues that exposure to a print-rich, learner-centric, and multilingual environment enables students to enhance their English language acquisition through meaning-focussed instruction, establish a complementary relationship between English and their home languages, and embrace learner autonomy and critical agency.
Access status: Metadata only ,
Incorporation of MXene into all-inorganic halide double perovskite and its influence on resistive switching behaviour
(AIP Publishing, 2026-09) Borgohain, Karabi Kanchan; Patra, Snigdha; Dehingia, Anurag; DAS, UJJAL; Roy, Asim
Mxene, a novel family of 2D materials, has gained significant attention due to its excellent properties like high electrical conductivity and mobility. Meanwhile, lead-free Cs2AgBiBr6 double perovskite (DP) has proved to be a magnificent active material for different optoelectronic applications. In our work, 2D Ti3C2Tx MXene is incorporated as an additive in Cs2AgBiBr6 DP to investigate its effects on the structural and optical properties of the DP. The pristine Cs2AgBiBr6 is synthesized using a one-step solution-processed method, and subsequently, Ti3C2Tx@Cs2AgBiBr6 composite is synthesized with different Ti3C2Tx additive concentrations, etched from its Ti3AlC2 MAX phase. The X-ray diffraction (XRD) pattern of the pure and Ti3C2Tx incorporated samples shows the typical face-centered cubic (FCC) structure of the Cs2AgBiBr6 DP crystal with change in average crystallite size at different Ti3C2Tx concentrations. The UV-vis-NIR absorption and Photoluminescence (PL) study is conducted to analyze the optical properties of the pristine and composites. The pristine Cs2AgBiBr6 DP shows an absorption edge at the visible regime with a band gap of 1.82 eV, while 2D Ti3C2Tx incorporation causes a slight shift in the absorption edge. Additionally, changes in the PL peak intensity of the DP specify the variation in its carrier recombination dynamics with different additive amounts. Furthermore, the resistive switching study of the DP shows that Ti3C2Tx incorporation improves the resistive switching performance by lowering the SET voltage in the fabricated memristive device. These structural and optical analyses of Ti3C2Tx @ Cs2AgBiBr6 composites and the improved resistive switching behaviour indicate its potential for future optoelectronic applications with optimized additive concentration.
Access status: Open Access ,
New Additions of Books - September 2026
(2026-09) Srinivasa Ramanujan Library
Access status: Open Access ,
Monthly Bulletin of New Publications - September 2026
(2026-09) Srinivasa Ramanujan Library
Access status: Open Access ,
Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation
(Association for Computational Linguistics, 2026-07) MULE, SRUJAN P.; Garikaparthi, Aniketh; Patwardhan, Manasi; Dept. of Data Science
As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and filtering hundreds of AI-generated ideas without exhaustive experimentation. We ask whether LMs can learn to forecast the empirical success of research ideas before any experiments are run. We study comparative empirical forecasting: given a benchmark-specific research goal and two candidate ideas, predict which will achieve better benchmark performance. We construct a dataset of 11,488 idea pairs grounded in objective outcomes from PapersWithCode. While off-the-shelf 8B-parameter models struggle (30% acc.), SFT dramatically boosts performance to 77.1%, outperforming GPT-5 (61.1%). By framing evaluation as a reasoning task via Reinforcement Learning with Verifiable Rewards (RLVR), we train models to discover latent reasoning paths, achieving 71.35% acc. with interpretable justifications. Through additional ablations and out-of-distribution tests, we show robustness to surface-level heuristics and transfer to both a cross-domain time-split test set and an independently constructed test set. Our results demonstrate that compute-efficient small language models can serve as effective, objective verifiers, offering a scalable path for autonomous scientific discovery.