Teaching and Learning

Teaching and Learning

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Leading the AI transformation in schools: it starts with a digital mindset - Educational technology research and development
Leading the AI transformation in schools: it starts with a digital mindset - Educational technology research and development
Rapid developments in artificial intelligence (AI) require dynamic adaptation in education to integrate new technologies timely and sustainably. In particular, the rise of generative AI requires leadership to implement it in a meaningful way for teaching and learning. School leaders have a special role to play in driving digital transformation. Based on a sample of German school leaders, this article explores how school leadership approaches and a digital mindset influence the implementation of AI in schools. Our findings provide initial and preliminary evidence that school leaders’ digital mindsets, particularly proactive agility and empathy, understood as perspective taking, influence the implementation of AI in schools. Furthermore, the findings highlight the effectiveness of ambidextrous leadership in driving AI implementation. As a consequence, our study paves the way for future explorations of the evolving landscape of AI in education and highlights the need for adaptive, empathetic, and proactive leadership in the digital age.
AIAI#AI#artificial intelligence#education#teaching and learning#digital mindset#school leaders#ambidextrous leadership
·link.springer.com·
Leading the AI transformation in schools: it starts with a digital mindset - Educational technology research and development
Assessing Visual Hallucinations in Vision-Enabled Large Language Models
Assessing Visual Hallucinations in Vision-Enabled Large Language Models
Recent advancements in vision-enabled large language models have prompted a renewed interest in evaluating their capabilities and limitations when interpreting complex visual data. The current research employs ImageNet-A, a dataset specifically designed with adversarially selected images that ...
AIAI#AI#artificial intelligence#vision-enabled large language models#visual hallucinations#ImageNet-A dataset
·researchsquare.com·
Assessing Visual Hallucinations in Vision-Enabled Large Language Models
The commodification of creativity: Integrating Generative Artificial Intelligence in higher education design curriculum
The commodification of creativity: Integrating Generative Artificial Intelligence in higher education design curriculum
The academic questions posed by the introduction of Generative AI (GenAI) into design higher education are many and reflect educators’uneasiness about its ethical use. Like any new radical technolo...
AIAI#AI#artificial intelligence#design#education#higher education#teaching
·tandfonline.com·
The commodification of creativity: Integrating Generative Artificial Intelligence in higher education design curriculum
Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment
Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment
The emergence of generative artificial intelligence (GenAI) requires innovative educational environments to leverage this technology effectively to address concerns like academic integrity, plagiarism, and others. Additionally, higher education needs effective pedagogies to achieve intended learning outcomes. This emphasizes the need to redesign active learning experiences in the GenAI era. Authentic assessment and experiential learning are two possible meaningful alternatives in this context. Accordingly, this article investigates how GenAI can enhance teaching and learning by constructively addressing study situations beyond conventional learning approaches and cultivating high-order skills and knowledge acquisition. This study employs thing ethnography to examine GenAI tools’ integration with authentic assessment and experiential learning and explore implementation alternatives. The results reveal insights into creating human-centered and GenAI-enhanced learning experiences within a constructive alignment. Specific examples are also provided to guide their implementation. Our contributions extend beyond the traditional use of GenAI tools as mere agents-to-write or agents-to-answer questions to become agents-to-support experiential learning for authentic assessment. These findings underscore the transformative role of GenAI tools in enhancing teaching and learning efficacy and effectiveness. The limitations in treating GenAI tools as subjects in thing ethnography are acknowledged, with potential for future implementation evaluation.
AIAI#AI#artificial intelligence#education#higher education#teaching and learning#assessment
·mdpi.com·
Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment
Summative assessment with Artificial Intelligence: Qualitative analysis and comparison of technology acceptance in student and teacher populations
Summative assessment with Artificial Intelligence: Qualitative analysis and comparison of technology acceptance in student and teacher populations
This qualitative study explores the levels of technology acceptance of students and teachers in higher education regarding the use of artificial intelligence (AI) in summative assessment. Twelve st...
AIAI#AI#artificial intelligence#education
·tandfonline.com·
Summative assessment with Artificial Intelligence: Qualitative analysis and comparison of technology acceptance in student and teacher populations
Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education - Danah Henriksen, Edwin Creely, Natalie Gruber, Sean Leahy, 2025
Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education - Danah Henriksen, Edwin Creely, Natalie Gruber, Sean Leahy, 2025
This article provides a critical thematic literature review that explores the intersection of generative artificial intelligence (GenAI) and social-emotional le...
AIAI#AI#artificial intelligence#education#pedagogy
·journals.sagepub.com·
Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education - Danah Henriksen, Edwin Creely, Natalie Gruber, Sean Leahy, 2025
Critical Thinking in the Age of AI
Critical Thinking in the Age of AI

Throughout human history, we have relied on technology to make our work easier. In this episode, Michelle Miller joins us to discuss how to foster students’ critical thinking skills in the age of AI.

Michelle is a Professor of Psychological Sciences and President’s Distinguished Teaching Fellow at Northern Arizona University. She is the author of Minds Online: Teaching Effectively with Technology, Remembering and Forgetting in the Age of Technology: Teaching, Learning, and the Science of Memory in a Wired World and A Teacher’s Guide to Learning Students’ Names: Why You Should, Why It’s Hard, How You Can. Michelle is also a frequent contributor of articles on teaching and learning in higher education to a variety of publications including The Chronicle of Higher Ed.

A transcript of this episode and show notes may be found at http://teaforteaching.com.

Throughout human history, we have relied on technology to make our work easier. In this episode, Michelle Miller joins us to discuss how to foster students’ critical thinking skills in the age of AI. Michelle is a Professor of Psychological Sciences and President’s Distinguished Teaching Fellow at Northern Arizona University.  She is the author of Minds Online: Teaching Effectively with Technology, Remembering and Forgetting in the Age of Technology: Teaching, Learning, and the Science of Memory in a Wired World and A Teacher’s Guide to Learning Students’ Names: Why You Should, Why It’s Hard, How You Can. Michelle is also a frequent contributor of articles on teaching and learning in higher education to a variety of publications including The Chronicle of Higher Ed. A transcript of this episode and show notes may be found at http://teaforteaching.com.
AIAI#higher education#pedagogy#podcast#teaching#teaching and learning#AI#education#technology#students
·podbean.com·
Critical Thinking in the Age of AI
1994 cupm maa quantitative reasoning for college graduates
1994 cupm maa quantitative reasoning for college graduates

Quantitative Reasoning for College Graduates: A Complement to the Standards

Mathematical Association of America

pp 9 of 36

In short, every college graduate should be able to apply simple mathematical methods to the solution of real-world problems. A quantitatively literate college graduate should be able to:

  1. Interpret mathematical models such as formulas, graphs, tables, and schematics, and draw inferences from them.
  2. Represent mathematical information symbolically, visually, numerically, and verbally.
  3. Use arithmetical, algebraic, geometric and statistical methods to solve problems.
  4. Estimate and check answers to mathematical problems in order to determine reasonableness, identify alternatives, and select optimal results.
  5. Recognize that mathematical and statistical methods have limits.
#assessment#higher education#pedagogy#students#teaching#teaching and learning#education#math#mathematics#learning#quantitative literacy#maa#Mathematical Association of America
·statlit.org·
1994 cupm maa quantitative reasoning for college graduates