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Category 1: Social Sciences Technology
Category 2: Technology
Author: Aryaveer Singh
Level of study[When the Paper was Published]: 10th
Description: Adolescents increasingly encounter news through algorithmically ranked feeds on video, messaging and social platforms rather than through mastheads, bulletins, or adult intermediaries. Ranking systems select and order what a young reader sees, yet the selection criteria are largely invisible, the sources are mixed, and fluent presentation is no guarantee of accuracy or independence. Meaningful news literacy in this environment therefore extends well beyond knowing that misinformation exists. It includes understanding that feeds are personalised, being able to establish who produced a claim and why, verifying consequential claims against independent evidence, calibrating trust to evidence rather than to presentation, recognising privacy and targeting risks, and behaving responsibly before resharing. This paper develops an academically grounded protocol for investigating these capacities among students in Classes IX and X in India. The proposed cross-sectional, multi-site survey uses a mixed-format instrument that combines objective knowledge items, self-reported competence, behavioural-frequency measures, scenario-based source-evaluation tasks, and a headline veracity discernment task. The conceptual model treats algorithmic news literacy as six related constructs: algorithmic and personalisation awareness, applied platform competence, source evaluation and verification, misinformation susceptibility, risk and ethical awareness, and responsible sharing behaviour. Device access, platform repertoire, language of news use, school context, and prior media-literacy instruction are treated as contextual predictors, while news trust and self-rated confidence are examined as calibration variables rather than as straightforward indicators of literacy. The protocol specifies a realistic independent-student sampling strategy, pilot testing, translation procedures, content and construct validation, reliability analysis, ethical safeguards for minors consistent with Indian data-protection expectations, and an analysis plan that accounts for school clustering and multiple comparisons. It also supplies participant materials, a complete draft questionnaire, and a variable-coding framework. No empirical findings are reported because primary data have not yet been collected. The study is designed to produce transparent, reproducible evidence about how Indian adolescents meet news, how they judge it, and what school-based instruction could strengthen safe, critical, and responsible participation. Keywords: algorithmic news literacy; media and information literacy; news personalisation; source evaluation; misinformation susceptibility; adolescents; India; secondary education; research protocol
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Category 1: Technology Social Sciences
Category 2: Social Sciences
Author: Aryaveer Singh
Level of study[When the Paper was Published]: 10th
Description: This research looks at how Indian secondary-school students understand and use generative AI. It focuses on four main areas: students’ awareness of AI, how they use these tools, whether they check the information AI provides, and how they perceive the risks involved. The study explores the ways students use generative AI for learning and schoolwork, as well as how well they recognize that AI-generated answers are not always accurate or reliable. It also examines whether students verify information before trusting or using it. Alongside these everyday practices, the research considers students’ understanding of broader concerns such as misleading or fabricated information, bias, privacy, misinformation, and academic integrity. By bringing these areas together, the study seeks to develop a better picture of how prepared secondary-school students are to use generative AI thoughtfully and responsibly, while identifying areas where additional guidance or AI-literacy education may be needed.
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