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Resources
We contribute to current and emerging public conversations and policy development related to edtech and AI in education. We also curate resources that we find helpful in navigating the rapidly growing domain of AI-enabled edtech.
Please note that inclusion in our curated list does not constitute endorsement of all the views in a resource.
If you would like to suggest a resource for potential inclusion, please contact us here.
Publications
Report: Towards high quality in Australian educational technology
To leverage the benefits of edtech for student learning, tools need to be well designed, effectively used, and appropriately governed, but in a rapidly growing sea of applications, how will we know when that is the case?
This report outlines how edtech increasingly is the mediating layer between curriculum and the classroom, highlighting the need for a national quality assurance process for educational technology (edtech) used in Australian classrooms.
Report: Shaping AI and edtech to tackle Australia’s learning divide
Professor Loble produced this report during her tenure as a Paul Ramsay Fellow, affiliated with the UTS Centre for Social Justice & Inclusion. Establishing the Australian Network for Quality Digital Education enacts the report’s first recommendation, and the report's insights will underpin the Network’s priorities.
Submission: Review to inform a better and fairer education system
The Australian Government established the Review to Inform a Better and Fairer Education System as part of the process to develop the next National School Reform Agreement, to lift student outcomes across Australian schools. Professor Loble's submission to the review focuses on the potential for education technology to play a role in improving equity of student outcomes, providing certain conditions are met.
The Australian Government is investigating the use of generative artificial intelligence in the Australian education system. In addition to making a formal submission to the inquiry, Professor Loble presented expert evidence at a public hearing.
Additional resources
Guidance for generative AI in education and research
UNESCO
2023
UNESCO's guidance takes a humanistic approach to assessing the risks as well as potential advantages of generative AI in education. It includes an accessible introduction to generative AI and how it works, as well as to the key controversies surrounding it, and a number of possible use cases. Key education takeaways include:
- Generative AI is currently unreliable, understanding 'neither the prompt nor the response,' and generative content purely on the basis of 'probabilities of language patterns' (p.26). Young learners are at particular risk of accepting output at face value.
- The implications of generative AI for knowledge creation, transmission and validation are still emerging, but foundational knowledge and skills, and higher-order thinking skills, will remain critical to ensure that humans can critically evaluate and engage with AI output.
- Any generative AI-based applications used in education should be 'educationally effective and valid for the ages and abilities of the target learners, and … aligned with sound pedagogical principles (i.e. based on the relevant domains of knowledge and the expected learning outcomes and development of values)' (p.25).
- Human agency, including the intrinsic motivation to learn, should be safeguarded.
- Teachers 'need to be supported to strengthen their capacities for the proper use of GenAI' (p.20).
Data Equity: Foundational Concepts for Generative AI Briefing Paper
World Economic Forum
2023
The World Economic Forum's briefing paper unpacks the concept of data equity -- 'a core notion within data governance centred on the impact of data on the equity of technical systems for individuals, groups, enterprises and ecosystems' (p.3) -- in the context of large language (also known as foundation) models. The paper identifies key equity considerations across the data lifecycle, specifically:
- Input data equity (the importance of accurate representation of diverse communities within training data, noting the 'intricate trade-offs' between representation and privacy concerns)
- Algorithmic data equity (the importance of ensuring that algorithms function as impartially and accurately as possible for all populations, noting the inherent challenges foundation models pose to algorithmic transparency, and the importance of AI literacy for understanding models; capabilities and limitations)
- Output data equity (the fairness of the models' tangible effects, noting the importance of equitable distribution of benefits).
Centre for Evidence and Implementation
2023
Singapore has focused strongly on the integration of technology across society, including education, for at least two decades. Following COVID, 'Singapore is transitioning to utilising technology in business-as-usual education delivery.' Technology is approached as a key lever for meeting the needs of the full range of learners, with a particular focus on students with disability. Nonetheless, Singapore faces a range of familiar challenges in seeking consistent, skillful implementation. Key takeaways:
- Students can use the Singapore Learning System at any time, to study any subject at any level and have their progress monitored. Teachers also integrate resources from this platform into their programs. Usage rates of 80% students and 70% teachers are reported.
- Student engagement concerns persist, and screen fatigue may be an issue.
- Teaching practices that integrate pedagogy and technology to create cognitive scaffolding for lower-progress students have been shown to impact positively on student self-efficacy and motivation to learn.
- Familiar challenges include: challenges in identifying, evaluating or curating high-quality content; pace of change; balancing the positive impact of technology with the downside of technological distractions for students; navigating variability in teacher attitudes to, confidence and competence with, technology; ensuring equity of access (though this issue appears to be on a lesser scale than other countries).
EdTech Developer's Guide: A primer for software developers, start-ups and entrepreneurs
Office of Educational Technology, U.S. Department of Education
2015
Despite being a few years old, this guide's identification of key opportunities for technology to support and improve teaching and learning still holds true. The guide draws significantly on teacher and educator perspectives, reinforcing the value of putting user perspectives at the heart of product design and development. Identified opportunities are:
- Improving mastery of academic skills
- Developing skills to promote lifelong learning
- Increasing family engagement
- Planning for future education opportunities
- Designing effective assessments
- Improving educator professional development
- Improving educator productivity
- Making learning accessible to all students
- Closing opportunity gaps
- Closing achievement gaps.
High-Dosage Tutoring at Scale: Evidence from a Cost-Effective, Blended-Learning Tutoring Model
University of Chicago Education Lab
2023
This study, in partnership with Chicago Public Schools, New York City Department of Education, and Saga Education, finds that incorporating an online mathematics application can effectively scale the benefits of in-person, small-group tutoring at reduced per-student cost. Students alternated between working directly with a tutor and working with an educational application. Participation in the hybrid model resulted in 1-2 years of additional mathematics learning, comparable with the results achieved by the original Saga model.
Stanford University students and personnel with U.S. high school teachers
The goal of the CRAFT program is to provide free, high-quality resources informed by learning sciences research for non-profit use by classroom educators.
News
- Australia needs quality assurance to harness benefits of AI and edtech for students and schools
- EdTech is booming. But is it any good?
- The rise of ChatGPT shows why we need a clearer approach to technology in schools
- New EdTech network to address educational inequality
- Stronger governance of edtech needed