Scenario-Based Training and On-The-Job Support for Equitable Mentoring

Thomas, Danielle R.; Chhabra, Pallavi; Adeniran, Adetunji; Kopko, Joseph; Tipper, Cindy; Gupta, Shivang; Koedinger, Kenneth R.

doi:10.1007/978-3-031-21569-8_54

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…The platform adapts in real-time to students' responses, providing personalized lessons. Pilot projects in U.S. schools showed positive results, with students demonstrating increased engagement and improvements in math proficiency (Chine et al, 2022). Zaya Learning Labs uses AI to deliver personalized and adaptive learning experiences to students in India (Kaur, 2016).…”

Section: Case Studies and Pilot Projects Of Ai In Education Globallymentioning

confidence: 99%

Review of Ai in Education: Transforming Learning Environments in Africa

Onyebuchi Nneamaka Chisom,

Chika Chioma Unachukwu,

Blessing Osawaru

2024

Int. j. appl. res. soc. sci.

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This study analyses artificial intelligence (AI's) impact on education in Africa, focusing on personalized learning, technology integration, and challenges in educational development. This review explores the transformative role of Artificial Intelligence (AI) in reshaping educational landscapes across Africa. As the continent strives for inclusive and quality education, AI emerges as a potent tool with the potential to address educational challenges, enhance learning outcomes, and bridge existing gaps. The review delves into various applications of AI in education, ranging from personalized learning experiences to adaptive assessment methodologies, and examines their impact on diverse learning environments. It gives an overview of the current state of education in Africa, the review highlights the disparities in access, quality, and infrastructure. It also investigates the innovative ways in which AI technologies are being integrated into educational systems. AI-powered adaptive learning platforms, virtual tutors, and intelligent content delivery systems are analyzed for their effectiveness in catering to the diverse needs of students across the continent. The review also addresses the potential of AI in overcoming language barriers, promoting literacy, and fostering digital skills development. Moreover, it explores the role of AI in facilitating teacher support, professional development, and administrative tasks, thereby contributing to the overall improvement of the education ecosystem. Ethical considerations, privacy concerns, and the digital divide are critically examined to ensure that the integration of AI in education aligns with ethical standards and promotes equitable access. Case studies and pilot projects from various African countries are presented to illustrate successful implementations, challenges faced, and lessons learned. Furthermore, the review discusses the importance of collaborative efforts involving governments, educational institutions, technology developers, and the private sector. Policy recommendations and strategic initiatives are explored to guide the responsible and sustainable integration of AI in education across the diverse socio-economic and cultural contexts prevalent in Africa. In conclusion, the review synthesizes the current state of AI in education in Africa, offering insights into its potential to revolutionize learning environments. The transformative power of AI in addressing educational challenges and fostering a culture of continuous improvement is underscored, paving the way for a more inclusive, accessible, and innovative education landscape in the African context. Keywords: Artificial Intelligence, Education, Transform Learning, Environments, Africa.

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Section: Case Studies and Pilot Projects Of Ai In Education Globallymentioning

confidence: 99%

Review of Ai in Education: Transforming Learning Environments in Africa

Onyebuchi Nneamaka Chisom,

Chika Chioma Unachukwu,

Blessing Osawaru

2024

Int. j. appl. res. soc. sci.

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“…Currently, there are more than 20 lessons housed in the PLUS app each aligning with competency areas of the SMART framework [25]. The lessons task tutors with predicting and explaining the most desired approach when responding to common tutoring situations in both a pretest and posttest, involving analogous scenarios [5][6]. Considerable evidence suggests that tutors benefit from scenario-based lesson instruction, focusing on specific tutor skills, with tutors performing significantly better at the posttest compared to the pretest when presented with similar tutoring scenarios [29].…”

Section: Tutor Training and Lesson Developmentmentioning

confidence: 99%

“…This training helps to ensure that tutors are prepared to engage with students in ways that contribute to their social emotional learning, while building strong relationships and encouraging a growth mindset over a fixed mindset. Presently, researchers are developing situational, scenario-based experiences for the training of adult tutors [6] and similar low-stakes, deliberate practice opportunities for teachers [26].…”

Section: Tutor Training and Lesson Developmentmentioning

confidence: 99%

“…Effective tutoring addresses students' challenges to motivation and engagement alongside mastering content and pedagogy [6,27,28]. To expand tutoring programs successfully, comprehensive, and ongoing training for adult tutors is needed, especially among volunteers, college students, and peers, who may lack pedagogical expertise and need support in relationship building [17].…”

Section: Introductionmentioning

confidence: 99%

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Using Generative AI to Provide Feedback to Adult Tutors in Training and Assess Real-life Performance

Thomas,

Gatz,

Gupta

et al. 2024

Preprint

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Tutoring remains among the most impactful academic interventions known to improve student achievement. Despite its success, there are few available opportunities for training and professional development for adult tutors. Furthermore, the task of assessing tutor performance during actual tutoring sessions is challenging and time-consuming for human evaluators—enter artificial intelligence (AI). In this work, we harness generative AI, specifi-cally large language models (LLMs) like GPT-4, to introduce an innovative approach for delivering tutors real-time, explanatory feedback while tutors engage in online scenario-based lessons. Hosted within the Personalized Learning Squared (PLUS) tutoring platform, these lessons offer tutors op-portunities to practice responding to common tutoring scenarios. For exam-ple, in the Giving Effective Praise lesson, tutors practice responding to students by providing praise and then receiving immediate and templated feedback generated by LLMs. Beyond demonstrating tutor training contain-ing AI-generated feedback, we report past work using LLMs to assess tutors providing praise, revealing moderate performance, and explaining several prompting methods. While using generative AI shows promise as a low-cost and efficient method for giving adult tutors feedback on their perfor-mance in training and actual tutoring, it is not without limitations. Practical and ethical considerations are discussed. Human tutoring remains a robust and irreplaceable influence on student learning, with generative AI serving as a valuable tool to complement tutors and enhance the impact of tutoring on student learning.

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