Our picks for the month of July
TeachWell gathers together timely reminders and a range of resources to support staff who lead and teach on courses.
Remember these important dates
- Semester Two: Monday 3 July, A friendly reminder to publish your Canvas course, two weeks prior to teaching.
- Semester Two: Monday 3 July, coursework and exam details. Course View is open for Faculty’s to update coursework and exam details.
- Quarter Three: Monday 3 July, make sure that SET eligible staff have Teacher role in Canvas.
- Semester One: Thursday 6 July, exam final results are due.
- Semester Two: Friday 14 July, coursework and exam details returned by departments via Course View.
- Teaching Catalyst: Thursday 20 July, enrolments close for Semester Two cohort.
- Quarter Three: Friday 28 July, exam timetable is published to students.
- Semester Two: Friday 28 July, make sure that SET eligible staff have Teacher role in Canvas.
Adding to your kete – sharing teaching practices
What does ‘good’ feedback mean?
Listening to students often gives us useful feedback and makes them active participants in the learning process. 6 themes and 28 concepts were identified in a survey conducted from 300 first-year Marketing students. The question of how to respond was answered with two possible solutions, focus on peer-based feedback and marking rubrics.
Have a look at case studies on how teachers at the University of Auckland are using feedback in practice. And how to write a good rubric.
A simple hack?
Does the purpose of your assessment require a written essay? Dave Sayers may have found an answer using Google Drive and Version History. The first thought that springs to mind is, “but the student can just copy what AI has written by typing it out.” The author argues that humans don’t type big blocks of text word for word, they will add bits, delete bits, move bits around and all this appears in the document version history.
Cybersecurity in Education: What Teachers, Parent and Students Should Know
Tips and Tricks on staying informed. Understand the best practices to protect yourself and students.
Assigning AI: Seven Approaches for Students, with Prompts
Ethan and Lilach Mollick take an opportunity approach towards Large Language Models (LLMs), seeing it as a supportive tool rather than a replacement. They propose a framework of seven approaches that can assist in classroom teaching. Their guidelines outline both benefits and risks of using AI and offer suggestions to increase student engagement by providing more time for active discussions and collaborative learning activities.
What do higher education students want from online learning?
Post COVID, which learning models to students favour? Remote, hybrid or on campus? McKinsey surveyed students from 17 countries and identified 8 key dimensions and 24 attributes that students desire from online learning. The following article outlines their findings.
What do higher education students want from online learning?