dc.contributor.author
Lochner, Katharina
dc.date.accessioned
2018-06-07T15:13:27Z
dc.date.available
2014-10-28T11:01:54.478Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/762
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-4964
dc.description
ACKNOWLEDGEMENTS ABSTRACT ZUSAMMENFASSUNG CONTENT INTRODUCTION 1\. CHAPTER 1:
ONLINE ASSESSMENT AND ONLINE SURVEYS 1.1. Definition, Advantages, and
Disadvantages 1.1.1. Advantages 1.1.2. Disadvantages 1.2. Quality of Online
Data 1.2.1. Equivalence of Paper-and-Pencil and Online Data 1.2.2. Fulfilment
of Test Quality Criteria 1.3. Representativeness of Online Studies 1.3.1.
Sampling 1.3.2. Retention 1.3.3. Standardisation and Controllability of the
Situation 1.4. Design of online studies 1.5. Summary CHAPTER 2: INTELLIGENCE
AND INTELLIGENCE TESTING 2.1. Models of Intelligence 2.1.1. Two-Factor
Theories 2.1.2. Primary factors 2.1.3. Integration of the models 2.1.4.
Multidimensional Model 2.1.5. Other Theories of Intelligence 2.1.6. Summary
2.2. Intelligence tests 2.2.1. Raven’s Progressive Matrices (RPM; Raven et
al., 2003) 2.2.2. Woodcock-Johnson Test of Cognitive Abilities (Woodcock et
al., 2001) 2.2.3. Berlin Intelligence Structure Test (BIS Test; Jäger et al.,
1997) 2.2.4. Adaptive Matrices Test (AMT; Hornke et al., 2000) 2.3. Summary
CHAPTER 3: AFFECT, MOOD, AND EMOTIONS 3.1. Models of Affect 3.1.1. Structural
Models 3.1.2. Models of Discrete Emotions 3.1.3. Hybrid Models 3.1.4. Domain-
Specific Models 3.2. Measurement of Mood and Emotions 3.2.1. Assessment of the
Physiological Component 3.2.2. Assessment of the Expressive Component 3.2.3.
Assessment of the Affective Component 3.3. Elicitation of Mood and Emotions
3.3.1. Overview of Mood and Emotion Elicitation Methods 3.3.2. Online Mood
Induction 3.3.3. Reviews of Mood and Emotion Induction Procedures 3.4. Summary
CHAPTER 4: AFFECT AND COGNITION 4.1. Affect and Cognition in the Brain 4.1.1.
Neuropsychological Theory of Positive Emotions (Ashby, Isen, & Turken, 1999)
4.1.2. Affect and Information Processing 4.2. Cognitive Approaches: Mood-
Induced Thinking Styles 4.2.1. The Theory of Personality Systems Interaction
(PSI Theory; Kuhl, 1983a, b) 4.2.2. Feelings-as-Information Theory (Schwarz,
1990) 4.2.3. Somatic Markers Hypothesis (Damasio, 1994) 4.2.4. Empirical
Findings on the Three Theories 4.3. Cognitive Approaches: Memory 4.3.1. Mood
Congruency and State Dependency (Bower, 1981) 4.3.2. Cognitive Context (Isen,
1984) 4.3.3. The Broaden-and-Build Theory of Positive Emotions (Fredrickson,
1998, 2001) 4.4. Attention-Theoretical Approaches 4.4.1. Cue Utilisation
(Easterbrook, 1959) 4.4.2. The Resource Allocation Model (Ellis & Ashbrook,
1988) 4.5. Activation-Theoretical Approaches 4.6. Motivational Approaches
4.6.1. Mood Maintenance and Mood Repair (Isen, 1984) 4.6.2. The Rubicon Model
of Action Phases (Heckhausen & Gollwitzer, 1986, 1987) 4.6.3. Expectancy
Theory (Vroom, 1964) 4.6.4. Seo, Barrett, and Bartunek’s (2004) Theory 4.7.
Task Demand-Based Approaches 4.7.1. The Multifactor-System Dynamics Theory of
Emotion (Royce & Diamond, 1980) 4.7.2. Dual-Force Model (Fiedler, 1990) 4.7.3.
Affect Infusion Model (AIM; Forgas, 1995) 4.8. An integrative Model: The
Cognitive-Motivational Mediator Model of the Impact of Mood on Cognitive
Performance (Abele, 1995) 4.8.1. Affect and Perceptual Speed 4.8.2. Affect and
Creativity 4.8.3. Affect and Reasoning 4.9. Discrete Emotions and Cognitive
Performance 4.10. Summary of Theories and Findings CHAPTER 5: THE PRESENT
STUDY 5.1. Hypotheses on Emotions and Test Performance 5.2. Considerations
about the Design of the Study 5.2.1. Selection of the Film Clips 5.2.2.
Manipulation Check CHAPTER 6: PILOT STUDIES 6.1. Pilot study 1: Design of an
Online Mood Questionnaire 6.2. Pilot study 1a: Validation of the Visual
Analogue Scale 6.2.1. Method 6.2.2. Results 6.2.3. Discussion 6.3. Pilot Study
1b: Refinement of the Visual Analogue Scale 6.3.1. Method 6.3.2. Results
6.3.3. Discussion 6.4. Pilot study 2: Design of an Online Questionnaire
Assessing Test-Related Emotions 6.4.1. Method 6.4.2. Results 6.4.3. Discussion
6.5. Manipulation Check using the Adapted Questionnaires 6.5.1. Expected
Effects on the Mood Dimensions 6.5.2. Expected Effects on Motivation and
Emotions CHAPTER 7: METHOD 7.1. Instruments Used 7.1.1. Mood 7.1.2. Test-
Related Emotions and Motivation 7.1.3. IQ Test Performance 7.1.4. Induction of
Emotional States 7.2. Procedure 7.2.1. Test Run 7.2.2. Experiment 7.3.
Participants CHAPTER 8: RESULTS 8.1. Drop-Out Effects 8.1.1. Demographic
Variables 8.1.2. Performance on the first test 8.2. Randomisation 8.2.1. Block
Randomisation 8.2.2. Differences with Respect to Demographic Variables 8.2.3.
Differences in Test Performance 8.2.4. Differences in Affectivity 8.3.
Relations Between Mood, Emotion, and Performance Before the Emotion Induction
8.3.1. Intercorrelations of Mood and Emotion 8.3.2. Correlations of Mood and
Emotion with Performance on the First Test 8.4. Manipulation Check 8.4.1.
Changes in Affectivity after the Emotion Induction 8.4.2. Comparisons on
Affectivity After the Induction 8.4.3. Change in Affectivity During the Test:
After Induction versus After Test 8.4.4. Change in Affectivity During the
Test: Before Induction versus After Test 8.5. Effects of Affective State on
Test Performance 8.5.1. Test Performance After the Emotion Induction 8.5.2.
Differences between the Scores on the Second Test 8.5.3. Effects of Emotion on
Test Performance 8.5.4. Structural Equation Models 8.5.5. Summary CHAPTER 9:
DISCUSSION 9.1. Impact of Emotions on Test Performance 9.1.1. Valence of Mood
or Emotions and Reasoning Test Performance 9.1.2. Activation of Mood or
Emotions and Reasoning Test Performance 9.1.3. Task Type, Mood and Emotion,
and Reasoning Test Performance 9.1.4. Impact of Emotions on Test Performance:
Limitations 9.1.5. Summary 9.2. Online Emotion Induction 9.2.1. Affective
State Before the Emotion Induction Procedure 9.2.2. Changes in Mood States due
to the Emotion Induction Procedure 9.2.3. Changes in Emotional States due to
the Emotion Induction Procedure 9.2.4. Changes in Mood States after the Test
9.2.5. Online Emotion Induction: Limitations 9.2.6. Online Emotion Induction:
Summary 9.3. Unsupervised Online Experiments 9.3.1. Sampling and Retention
9.3.2. Data Quality 9.3.3. Unsupervised Online Experiments: Limitations 9.3.4.
Unsupervised Online Experiments: Summary 9.4. Summary and Conclusions 9.5.
Outlook and Future Research REFERENCES TABLES FIGURES APPENDIX A APPENDIX B
APPENDIX C APPENDIX D APPENDIX E APPENDIX F APPENDIX G ERKLÄRUNG
dc.description.abstract
In personnel selection there is an ongoing trend towards the use of
unsupervised online ability testing (Bateson, Wirtz, Burke, & Vaughan, 2013;
cut-e Group, 2012; Lievens & Harris, 2003). The assumption is that the tests
measure cognitive ability. However, performance on such tests has been found
to be influenced by mood (Lyubomirski, King, & Diener, 2005). Results are
contradictory because sometimes positive (Abele, 1995; Radenhausen & Anker,
1988) and sometimes negative mood (Melton, 1995) has been found to improve
test performance. Specific emotions like joy or anger have only been studied
in the context of academic performance (Pekrun, Elliot, & Maier, 2009), and
there are no studies on the impact of mood or emotions on performance in
unsupervised online testing. Therefore, the purpose of the present study was
to investigate the impact of specific emotions on performance on a reasoning
test in an unsupervised online experiment. Hypotheses were that performance
would be (1) better in joy than in anger, (2) better in contentment than in
sadness, (3) better in joy than in contentment, and (4) better in anger than
in sadness. A diverse sample of 429 participants completed an online reasoning
test, once before and once after the induction of one of the five emotional
states of joy, anger, sadness, contentment, or neutral, respectively. The
induction procedure successfully evoked distinct emotional states. Contrary to
the hypotheses, however, the experimentally manipulated emotions did not
affect performance on the online reasoning test, which might be attributable
to reasoning tests being less susceptible to the influence of emotions than
other types of tests (Fiedler, 1990; Forgas, 1995; Royce & Diamond, 1988).
There is also the possibility that the effects of affective state on test
performance were too weak to be detected in the comparatively unstandardised
situation and the diverse sample (Stanton, 1998). Another possibility is that
participants entered a state of flow (Czikszentmihalyi, Abuhamdeh, & Nakamura,
2007) in which thoughts or feelings do not interfere with the task.
de
dc.description.abstract
In der Personalauswahl werden vermehrt unüberwachte Online-Fähigkeitstests
eingesetzt (Bateson, Wirtz, Burke, & Vaughan, 2013; cut-e Group, 2012; Lievens
& Harris, 2003). Die Annahme ist, dass diese Tests kognitive Fähigkeiten
messen. Verschiedenen Studien zufolge werden die Testergebnisse allerdings
auch von der Stimmung beeinflusst (Lyubomirski, King, & Diener, 2005). Die
Befunde sind widersprüchlich: In einigen Studien ist die Leistung in positiver
Stimmung besser (Abele, 1995; Radenhausen & Anker, 1988), in anderen in
negativer Stimmung (Melton, 1995). Diskrete Emotionen wie Freude oder Ärger
wurden bisher nur im akademischen Kontext untersucht (Pekrun, Elliot, & Maier,
2009), während es gar keine Studien zu unüberwachten Online-Tests gibt. Daher
untersucht die vorliegende Arbeit den Einfluss diskreter Emotionen auf die
Leistung in einem unüberwachten Online-Fähigkeitstest, der logisches Denken
erfasst. Die Hypothesen waren, dass die Leistung (1) in Freude besser ist als
in Ärger, (2) in Gelassenheit besser ist als in Traurigkeit, (3) in Freude
besser ist als in Gelassenheit und (4) in Ärger besser ist als in Traurigkeit.
429 Teilnehmer verschiedenen Alters und Bildungsgrades bearbeiteten einen
Online-Test, der schlussfolgerndes Denken erfasst, einmal vor und einmal nach
der Induktion einer der Emo-tionen Freude, Trauer, Ärger, Gelassenheit oder
eines neutralen emotionalen Zustandes. Die Filme erzeugten diskrete Emotionen.
Anders als erwartet hatten die verschiedenen emotionalen Zustände jedoch
keinen Einfluss auf die Testleistung. Mögliche Gründe für den Befund sind,
dass schlussfolgerndes Denken nur in geringem Maße von Emotionen beeinflusst
wird (Fiedler, 1990; Forgas, 1995; Royce & Diamond, 1988), dass es aufgrund
der breiten Stichprobe und des unüberwachten Settings andere Varianzquellen
gibt, welche den Einfluss der Emotionen überlagern (Stanton, 1998) oder dass
die Teilnehmer während der Testung einen Zustand des Flow erlebten
(Czikszentmihalyi, Abuhamdeh, & Nakamura, 2007), in dem Gedanken und Gefühle
keinen Einfluss auf die Aufgabenbearbeitung haben.
de
dc.format.extent
XV, 359 S.
dc.rights.uri
http://www.fu-berlin.de/sites/refubium/rechtliches/Nutzungsbedingungen
dc.subject
Online Assessment
dc.subject
Positive Psychology
dc.subject
Mood Induction
dc.subject
Online Experiment
dc.subject
Intelligence Test
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::152 Sinneswahrnehmung, Bewegung, Emotionen, Triebe
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::153 Kognitive Prozesse, Intelligenz
dc.subject.ddc
100 Philosophie und Psychologie
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::155 Differentielle Psychologie, Entwicklungspsychologie
dc.title
Emotions and Cognitive Performance
dc.contributor.contact
katharina.lochner@cut-e.com
dc.contributor.firstReferee
Prof. Dr. Michael Eid
dc.contributor.furtherReferee
Prof. Dr. Rudolf Kerschreiter
dc.date.accepted
2014-06-27
dc.identifier.urn
urn:nbn:de:kobv:188-fudissthesis000000097640-5
dc.title.subtitle
The Impact of Test Takers' Emotions on Performance in Online Assessment
dc.title.translated
Emotionen und kognitive Leistung
de
dc.title.translatedsubtitle
Der Einfluss von Emotionen auf die Leistung im Online Assessment
de
refubium.affiliation
Erziehungswissenschaft und Psychologie
de
refubium.mycore.fudocsId
FUDISS_thesis_000000097640
refubium.mycore.derivateId
FUDISS_derivate_000000015900
dcterms.accessRights.dnb
free
dcterms.accessRights.openaire
open access