#68,793 | AsPredicted

'Comics_Education02 (or Geschichten verstehen 02)'
(AsPredicted #68,793)


Author(s)
Irina Brich (Leibniz-Institut für Wissensmedien, Tübingen) - i.brich@iwm-tuebingen.de
Ekaterina Varkentin (Leibniz-Institut für Wissensmedien, Tübingen) - e.varkentin@iwm-tuebingen.de
Natalia Gagarina (Leibniz-Zentrum Allgemeine Sprachwissenschaft, Berlin) - gagarina@leibniz-zas.de
Markus Huff (Eberhard-Karls-Universität Tübingen) - markus.huff@uni-tuebingen.de
Pre-registered on
2021/06/18 08:04 (PT)

1) Have any data been collected for this study already?
No, no data have been collected for this study yet.

2) What's the main question being asked or hypothesis being tested in this study?
This study aims to test the influence of age and education on narrative comprehension in a representative sample. It will investigate bridging inference generation i.e., inferences generated to bridge gaps in the narration during the viewing of pictorial and textual narratives. The main question is whether participants in various education and age groups significantly differ in narrative comprehension and whether there is a general comprehension skill with regard to codality (i.e., no comprehension differences between pictorial and textural stories).
We expect…
a) narrative comprehension to increase with higher education.
b) narrative comprehension to decrease with higher age.
c) no difference in the comprehension of textual and pictorial narratives and this should not be influenced by education or age (education and age effects do not interact with story codality).

3) Describe the key dependent variable(s) specifying how they will be measured.
Narrative Comprehension: measured as the correct identification of true (describing the correct inference for the missing bridging event) and false (describing a wrong inference for the missing bridging event) inference statements (incorrect answer = 0, correct answer =1).

Secondary measure confidence corrected narrative comprehension: includes a metacognitive measure assessed through the confidence rating for the answer to the inference identification. Confidence ("Wie sicher sind Sie sich bei Ihrer Antwort?) is given on a 6 point-scale (sehr unsicher, unsicher, eher unsicher, eher sicher, sicher, sehr sicher). Answers will be scored from 1 to 12 points. For incorrect answers (1-6 points): Highly confident incorrect answers receive 1 point, highly unconfident incorrect answers receive 6; For correct answers (7-12 points): highly unconfident correct answers receive 7 points, highly confident correct answers receive 12.

4) How many and which conditions will participants be assigned to?
The study has a 3 education (with low, middle, high) x age (continuous) x 2 codality (text, picture) design. The codality variable will be manipulated within subjects. Education and age (between-subjects) will be assessed during the experiment and education will be grouped into different groups/levels. A prescreening questionnaire assures a representative quota sample with regard to age, education, and gender.

The classification of education into low, middle, and high will be based on a question asking for school education.
- Low education will include: „Noch Schüler", „Schule beendet ohne Abschluss", „Haupt-/Volksschulabschluss, Abschluss Polytechnische Oberschule 8. Klasse"
- Middle education will include: „Realschulabschluss (Mittlere Reife), Abschluss Polytechnische Oberschule 10. Klasse"
- High education will include: „Fachhochschulreife (Abschluss nach 12. bzw. 11. Klasse, wenn kein Abitur), Abschluss an Berufsschulen, Fachkollegs, Fachabitur", „Abitur, Abschluss erweiterte Oberschule, Hochschulreife"

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Narrative comprehension will be analyzed with generalized linear mixed-effects models (glmer) through two step-wise model comparisons for the effects of education and age. Each glmer will include random intercepts for participant and story-clip. For the effects of education, model comparison begins with an intercept model predicting narrative comprehension and step by step the predictors for education, codality, and the interaction of education and codality will be added. Analogous model comparisons will be made for the effects of age (the continuous age variable will be centralized for analysis).

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
For data cleanup, all participants with a completion time below 3 and above 26 minutes will be excluded from the sample.

7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined.

A representative German sample of 1400 participants will be recruited through an online-panel provider. For data cleanup, around 10% of the specified sample will be recruited in addition. All participants (with complete datasets) remaining after data cleanup will comprise the sample for this study.

8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)

A secondary analysis will be conducted for the confidence corrected narrative comprehension measure. Confidence corrected narrative comprehension will be analyzed with linear mixed-effects models (lmers with random intercepts for participant and story-clip) through step-wise model comparisons for the effects of education and age. Analysis (i.e., model comparisons) will follow the procedure described for narrative comprehension.

We will conduct another secondary analysis with a different education classification including professional education levels: education will include 3 levels (low, middle, high) comprised of combinations of school education and professional education:
- Low education will include: Ohne Abschluss/Noch Schüler*in; Haupt-/Realschulabschluss ohne berufliche Ausbildung
- Middle education will include: Haupt-/Realschulabschluss und berufliche Ausbildung; FH-Reife/Abitur ohne berufliche Ausbildung
- High education will include: FH-Reife/Abitur und berufliche Ausbildung, Abschluss Berufs-/Fachakademie, FH-/ Universitätsabschluss
All analyses for narrative comprehension and confidence corrected narrative comprehension containing education will be repeated with this alternative education classification.

An explorative analysis will look into interactions between education, age, and codality.

We also assess participants' experience with pictorial and textual narrations and self-reported reading ability. Exploratory analyses will include these variables into the analyses for (confidence corrected) narrative comprehension.

Version of AsPredicted Questions: 2.00