Wider Reading for Learning Walkers and Lesson Observers (etc.)

It’s a truth well known, although occasionally forgotten, that evaluating teaching and learning is complex.  With that in mind, please see below for some wider reading that might be of interest when considered alongside Professor Robert Coe’s poor proxies for learning list.

Click here to access a handout with everything on.

Observations provide a snapshot, not a big picture

A single observation is unlikely to reflect a teacher’s broader repertoire of practices, and multiple observations sampled across time and content would likely better assess instructional quality.’

Try reading: Building a More Complete Understanding of Teacher Evaluation Using Classroom Observations, by Julie Cohen and Dan Goldhaber (2016)

Context really matters

Teachers were more than twice as likely to be rated in the top performance quintile if assigned the highest achieving students compared with teachers assigned the lowest achieving students.’

Try reading: What Do Teacher Observation Scores Really Measure?, by Matthew Steinberg and Rachel Garrett (2016)

Student engagement is a weak proxy for learning

Children’s inherent motivational dispositions and activity preferences are likely to be at odds with the need to engage in […] procedures that promote academic learning.’

Try reading: Folk Knowledge and Academic Learning, by David Gearey (2012)

Be cautious of taking student feedback at face value

‘Any substantive correlations between SET (Student Evaluation of Teaching) and learning are likely to be a fluke or an artefact rather than due to students’ ability to accurately assess instructor teaching effectiveness.’

Try reading: Student evaluation of teaching ratings and student learning are not related, by Bob Uttl et al. (2016)

Beware of over-confidence

A feeling of knowing is often only weakly predictive of actual knowledge and appears to be informed, at least in part, by top-down inferences about what should be or probably is known.’

Try reading: When Knowledge Knows No Bounds: Self-Perceived Expertise Predicts Claims of Impossible Knowledge, by Stav Atir et al. (2015)

Thanks for reading –





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