Introduction to Interviewing
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The document discusses the process of conducting interviews which includes 7 stages: determining the theme, designing how knowledge will be obtained, conducting interviews carefully, transcribing the interviews into text, analyzing based on the investigation type, verifying the findings, and reporting the results ethically. It also outlines different types of interview questions such as introductory, follow up, probing, specifying, direct, indirect, structuring, interpreting, and clarifying questions.
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The document outlines several techniques for analyzing interviews, including meaning analysis which involves coding text segments by theme, condensing sentences, and adding context. It also discusses language analysis such as linguistics, conversation analysis treating the interview as a conversation, and narrative analysis treating it as a story. Finally, it mentions eclectic analysis techniques like using multiple techniques together or creating a theoretical reading of the text.
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ChatGPT is an AI chatbot created by Anthropic to be helpful, harmless, and honest. It uses a transformer algorithm trained on millions of text conversations to identify patterns and relationships between words. While ChatGPT appears intelligent in its responses, it does not truly understand language and can be fooled. Several tools like GPT-ZERO exist to detect ChatGPT responses with high accuracy, but its answers can be modified to evade detection. The document recommends assignment designs that require skills beyond ChatGPT's abilities, like judgment, current events, group work, or multimedia submissions.
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- Evidence such as facts, documentation, and expert testimony can be used to justify beliefs and claims. The person making a claim has the burden of proof.
- Arguments follow basic logical rules like identity, non-contradiction, and excluded middle. They involve presenting a claim, evidence for the claim, and accepting or rejecting the claim.
- Common logical fallacies that invalidate arguments are discussed, like appeals to probability, false equivalences, and slippery slopes. Different types of arguments like deductive and inductive are also introduced.
Evaluating Teaching: SECTIONS
Evaluating Teaching: SECTIONS.
Check out:
Bates, A. W., & Poole, G. (2003). Effective Teaching with Technology in Higher Education: Foundations for Success. Jossey-Bass, An Imprint of Wiley. 10475 Crosspoint Blvd, Indianapolis, IN 46256.
Evaluating Teaching: MERLOT
The document outlines the three stages that are evaluated for educational software in the MERLOT Model:
1. Quality of Content - Evaluates whether the concepts, models and skills presented are valid and educationally significant for the discipline. Content should be core curriculum that is difficult to teach and learn.
2. Potential Effectiveness as a Teaching-Learning Tool - Evaluates if the software is likely to improve teaching and learning based on how faculty and students could use it. It should support multiple stages of the learning process and have clear learning objectives tailored for the target learners.
3. Ease of Use - Evaluates how easy it is for users to use the software for the first time. It should
Evaluating Teaching: Anstey and Watson Rubric
Evaluating Teaching: Anstey and Watson Rubric
Check out:
Lauren M. Anstey & Gavan P.L. Watson. (2018), Rubric for eLearning Tool Evaluation. Centre for Teaching and Learning, Western University,
http://creativecommons.org/licenses/by-n c-sa/4.0/
Evaluating Teaching: LORI
The document outlines 9 stages of the LORI model for evaluating educational technologies. The stages include evaluating the content quality, alignment of learning goals, ability to provide adaptive feedback, motivation of learners, design of visual and auditory presentations, ease of navigation and interface usability, accommodation of disabled learners, reusability across contexts, and compliance with international standards.
Designing Teaching: Pause Procedure
Designing Teaching: Pause Procedure
Check out:
https://www.researchgate.net/profile/Richa-Thaman/publication/266746579_Effective_Use_of_Pause_Procedure_to_Enhance_Student_Engagement_and_Learning/links/5b274a23458515270fd5bc38/Effective-Use-of-Pause-Procedure-to-Enhance-Student-Engagement-and-Learning.pdf
Designing Teaching: ADDIE
Designing Teaching: ADDIE
Check out:
https://www.researchgate.net/profile/Michael-Molenda/publication/251405713_In_search_of_the_elusive_ADDIE_model/links/5b5f098ba6fdccf0b200e5b2/In-search-of-the-elusive-ADDIE-model.pdf
Designing Teaching: ASSURE
Designing Teaching: ASSURE
Check out:
Heinich, R., Molenda, M., & Russell, J. D., (1993). Instructional Media and The New
Technologies of Instruction. New York: Macmillan
Designing Teaching: Laurilliard's Learning Types
Designing Teaching: Laurilliard's Learning Types
Check out:
Laurillard, D., 2013. Teaching as a design science: Building pedagogical patterns for learning and technology. Routledge.
Designing Teaching: Gagne's Nine Events of Instruction
Designing Teaching: Gagne's Nine Events of Instruction
Check out:
Gange, R.M., 1961. "The Conditions of Learning"
Designing Teaching: Elaboration Theory
Designing Teaching: Elaboration Theory
Check out:
Reigeluth, C. & Stein, F. (1983). The elaboration theory of instruction. In C. Reigeluth (ed.), Instructional Design Theories and Models. Hillsdale, NJ: Erlbaum Associates.
Universally Designed Learning Spaces: Some Considerations
This document discusses creating inclusive learning environments in higher education. It provides an overview of universal design principles and how they can be applied to different learning spaces on a university campus. The document outlines a process for applying universal design that involves identifying best practices, considering user diversity, merging with universal design models, planning accommodations, and getting feedback. It notes common reasons for reluctance to universal design and provides examples of accessibility features for physical spaces.
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