Evidence map›Paper›PMID 36772223›Full record

ArticleSensors (Basel, Switzerland)2023

A Study on the Role of Affective Feedback in Robot-Assisted Learning.

Gabriela Błażejowska, Łukasz Gruba, Bipin Indurkhya, Artur Gunia

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Editorial for the Special Issue Recognition Robotics.Sensors (Basel, Switzerland) · 2023
    Article
  3. Article
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

4 authors.

Gabriela BłażejowskaNextbank Software, 30-085 Krakow, Poland.
Łukasz GrubaKitopi, 30-383 Krakow, Poland.
Bipin IndurkhyaCognitive Science Department, Institute of Philosophy, Jagiellonian University, 31-007 Krakow, Poland.ORCID 0000-0002-3798-9209
Artur GuniaCognitive Science Department, Institute of Philosophy, Jagiellonian University, 31-007 Krakow, Poland.ORCID 0000-0002-4186-5516

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, there have been many approaches to using robots to teach computer programming. In intelligent tutoring systems and computer-aided learning, there is also some research to show that affective feedback to the student increases learning efficiency. However, a few studies on the role of incorporating an emotional personality in the robot in robot-assisted learning have found different results. To explore this issue further, we conducted a pilot study to investigate the effect of positive verbal encouragement and non-verbal emotive behaviour of the Miro-E robot during a robot-assisted programming session. The participants were tasked to program the robot's behaviour. In the experimental group, the robot monitored the participants' emotional state via their facial expressions, and provided affective feedback to the participants after completing each task. In the control group, the robot responded in a neutral way. The participants filled out a questionnaire before and after the programming session. The results show a positive reaction of the participants to the robot and the exercise. Though the number of participants was small, as the experiment was conducted during the pandemic, a qualitative analysis of the data was carried out. We found that the greatest affective outcome of the session was for students who had little experience or interest in programming before. We also found that the affective expressions of the robot had a negative impact on its likeability, revealing vestiges of the uncanny valley effect.

Indexed as

RoboticsEmotionsFeedbackHumansLearningPilot Projectsaffective computingemotion recognitionhuman–robot interactionMiro-Eprogramming educationsocial robots

Identifiers

PMID36772223
PMCPMC9918924

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.