arXiv subjects

Amy Ogan

Publications and source records attributed to Amy Ogan.

9 recordsLinked to original sources

arXiv2026

Language Preferences and Practices in Multilingual EdTech: Flexible Primary Language Use with Secondary Language Support

The benefits of learning in one's mother tongue are well documented, yet colonial languages dominate education, marginalizing local languages and limiting access for learners who rely on their mother tongue for understanding. With the rapid growth of educational technology, there is potential to integrate multilingual instruction supporting both colonial and local languages. This study is part of a larger quasi-experiment conducted in Uganda, where learners could choose to learn in English, Leb-Lango (a local language), or in Hybrid mode (a combination of both) in a remote EdTech course. We examined how learners who chose the Hybrid option navigated English and Leb-Lango. While many Hybrid learners did not consistently use both languages, those who did persisted longer in the course. Learners also shared how they managed language complexities. We provide the first empirical evidence of learner agency in bilingual remote EdTech instruction and offer insights for designing inclusive multilingual learning solutions.

cs.HC↗

arXiv2026

Inclusive Mobile Learning: How Technology-Enabled Language Choice Supports Multilingual Students

Most learners worldwide are multilingual, yet implementing multilingual education remains challenging in practice. EdTech offers an opportunity to bridge this gap and expand access for linguistically diverse learners. We conducted a quasi-experiment in Uganda with 2,931 participants enrolled in a non-formal radio- and mobile-based engineering course, where learners self-selected instruction in Leb Lango (a local language), English, or a Hybrid option combining both languages. The Leb Lango version of the course was used disproportionately by learners from rural areas, those with less formal education, and those with lower prior knowledge, broadening participation among disadvantaged learners. Moreover, the availability of Leb Lango instruction was associated with higher active participation, even among learners who registered for English instruction. Although Leb Lango learners began with lower performance, they demonstrated faster learning gains and achieved comparable final examination outcomes to English and Hybrid learners. These results suggest that providing local language options to learners is an effective way to make EdTech more accessible.

cs.HC↗

arXiv2025

Investigating Youth AI Auditing

Youth are active users and stakeholders of artificial intelligence (AI), yet they are often not included in responsible AI (RAI) practices. Emerging efforts in RAI largely focus on adult populations, missing an opportunity to get unique perspectives of youth. This study explores the potential of youth (teens under the age of 18) to engage meaningfully in RAI, specifically through AI auditing. In a workshop study with 17 teens, we investigated how youth can actively identify problematic behaviors in youth-relevant ubiquitous AI (text-to-image generative AI, autocompletion in search bar, image search) and the impacts of supporting AI auditing with critical AI literacy scaffolding with guided discussion about AI ethics and an auditing tool. We found that youth can contribute quality insights, shaped by their expertise (e.g., hobbies and passions), lived experiences (e.g., social identities), and age-related knowledge (e.g., understanding of fast-moving trends). We discuss how empowering youth in AI auditing can result in more responsible AI, support their learning through doing, and lead to implications for including youth in various participatory RAI processes.

cs.HC↗

arXiv2025

Applying Think-Aloud in ICTD: A Case Study of a Chatbot Use by Teachers in Rural C\^ote d'Ivoire

Think-alouds are a common HCI usability method where participants verbalize their thoughts while using interfaces. However, their utility in cross-cultural settings, particularly in the Global South, is unclear, where cultural differences impact user interactions. This paper investigates the usability challenges teachers in rural C\^ote d'Ivoire faced when using a chatbot designed to support an educational program. We conducted think-aloud sessions with 20 teachers two weeks after a chatbot deployment, analyzing their navigation, errors, and time spent on tasks. We discuss our approach and findings that helped us identify usability issues and challenging features for improving the chatbot designs. Our note summarizes our reflections on using think-aloud and contributes to discussions on its culturally sensitive adaptation in the Global South.

cs.HC↗

arXiv2024

Does the Doer Effect Exist Beyond WEIRD Populations? Toward Analytics in Radio and Phone-Based Learning

The Doer Effect states that completing more active learning activities, like practice questions, is more strongly related to positive learning outcomes than passive learning activities, like reading, watching, or listening to course materials. Although broad, most evidence has emerged from practice with tutoring systems in Western, Industrialized, Rich, Educated, and Democratic (WEIRD) populations in North America and Europe. Does the Doer Effect generalize beyond WEIRD populations, where learners may practice in remote locales through different technologies? Through learning analytics, we provide evidence from N = 234 Ugandan students answering multiple-choice questions via phones and listening to lectures via community radio. Our findings support the hypothesis that active learning is more associated with learning outcomes than passive learning. We find this relationship is weaker for learners with higher prior educational attainment. Our findings motivate further study of the Doer Effect in diverse populations. We offer considerations for future research in designing and evaluating contextually relevant active and passive learning opportunities including leveraging familiar technology, increasing the number of practice opportunities, and aligning multiple data sources.

cs.CY↗

arXiv2024

Children's Overtrust and Shifting Perspectives of Generative AI

The capabilities of generative AI (genAI) have dramatically increased in recent times, and there are opportunities for children to leverage new features for personal and school-related endeavors. However, while the future of genAI is taking form, there remain potentially harmful limitations, such as generation of outputs with misinformation and bias. We ran a workshop study focused on ChatGPT to explore middle school girls' (N = 26) attitudes and reasoning about how genAI works. We focused on girls who are often disproportionately impacted by algorithmic bias. We found that: (1) middle school girls were initially overtrusting of genAI, (2) deliberate exposure to the limitations and mistakes of generative AI shifted this overtrust to disillusionment about genAI capabilities, though they were still optimistic for future possibilities of genAI, and (3) their ideas about school policy were nuanced. This work informs how children think about genAI like ChatGPT and its integration in learning settings.

cs.HC↗

arXiv2024

ClassInSight: Designing Conversation Support Tools to Visualize Classroom Discussion for Personalized Teacher Professional Development

Teaching is one of many professions for which personalized feedback and reflection can help improve dialogue and discussion between the professional and those they serve. However, professional development (PD) is often impersonal as human observation is labor-intensive. Data-driven PD tools in teaching are of growing interest, but open questions about how professionals engage with their data in practice remain. In this paper, we present ClassInSight, a tool that visualizes three levels of teachers' discussion data and structures reflection. Through 22 reflection sessions and interviews with 5 high school science teachers, we found themes related to dissonance, contextualization, and sustainability in how teachers engaged with their data in the tool and in how their professional vision, the use of professional expertise to interpret events, shifted over time. We discuss guidelines for these conversational support tools to support personalized PD in professions beyond teaching where conversation and interaction are important.

cs.HC↗

arXiv2023

Making Sense of Machine Learning: Integrating Youth's Conceptual, Creative, and Critical Understandings of AI

Understanding how youth make sense of machine learning and how learning about machine learning can be supported in and out of school is more relevant than ever before as young people interact with machine learning powered applications everyday; while connecting with friends, listening to music, playing games, or attending school. In this symposium, we present different perspectives on understanding how learners make sense of machine learning in their everyday lives, how sensemaking of machine learning can be supported in and out of school through the construction of applications, and how youth critically evaluate machine learning powered systems. We discuss how sensemaking of machine learning applications involves the development and integration of conceptual, creative, and critical understandings that are increasingly important to prepare youth to participate in the world.

cs.CY↗

arXiv2023

Investigating Girls' Perspectives and Knowledge Gaps on Ethics and Fairness in Artificial Intelligence in a Lightweight Workshop

Artificial intelligence (AI) is everywhere, with many children having increased exposure to AI technologies in daily life. We aimed to understand middle school girls' (a group often excluded group in tech) perceptions and knowledge gaps about AI. We created and explored the feasibility of a lightweight (less than 3 hours) educational workshop in which learners considered challenges in their lives and communities and critically considered how existing and future AI could have an impact. After the workshop, learners had nuanced perceptions of AI, understanding AI can both help and harm. We discuss design implications for creating educational experiences in AI and fairness that embolden learners.

cs.HC↗