Evidence map›Paper›PMID 38625174›Full record

ArticleEducational research for policy and practice2023

From face-to-face to remote evaluation of teacher-education candidates during the COVID-19 pandemic.

Judy Goldenberg, Doron Niv

Abstract read
In one paragraph

Article in Educational research for policy and practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Judy GoldenbergTalpiot Academic College of Education, Holon, Israel.ORCID 0000-0002-8104-0869
Doron NivThe Mofet Institute, Tel Aviv-Yafo, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although teacher's personality is an essential component of successful classroom learning, most teacher education programs accept students solely on the basis of scholastic ability scores such as school grades, national test scores (SAT, GRE) or undergraduate college transcripts. To ensure suitability to teaching, a personality-evaluation system was developed in Israel for teacher education candidates. This evaluation system includes non-cognitive measures, such as group dynamic exercises, simulations, a teaching exercise, situational judgement tests, personality tests and an inter-personal interview, all performed face-to-face (FTF) at a testing center. The outbreak of COVID-19 in 2020 brought about lockdowns and social distancing, precluding the administration of this FTF evaluation system. Therefore, the development team adapted the system to online remote testing, using Zoom technology. The present study examined the effect of this transition to remote evaluation on the quality of selection for teaching, looking at suitability-to-teaching scores and the subjective views of applicants and evaluators. A comparison of the 2020 remote scores with the 2019 FTF scores revealed that scores on remote evaluation were slightly lower than FTF scores, and were more centralized. While the candidates found that remote evaluation provided fewer opportunities to express themselves, both candidates and evaluators were satisfied with the administration and convenience of the evaluation day. The Discussion chapter summarizes the unique affordances and constraints of remote evaluations and presents suggestions for changes which might be made when moving an assessment online that could take advantage of this new environment.

Indexed as

COVID-19 pandemicMESILARemote testingTeacher-education studies

Identifiers

PMID38625174
PMCPMC10199659

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.