Oral Presentation at the ESERA Conference 2017 in Dublin. Abstract: In this study, we investigated the influence of textbook images on first year high school and middle school students' drawings about change of seasons. Participating students were first taught with a short curriculum sequence about change of seasons. Then, after three months, students were randomly assigned to a treatment and control group and asked to make a drawing and write an explanation of the phenomenon. Students of the treatment group were shown a typical textbook image before completing the task. Overall, 373 students (treatment group=193; control group=180) completed the task. Drawings were analyzed using factor analysis to identify emerging models. Results indicate that, while treatment and control groups students did not differ in knowledge about change of seasons, the image significantly influenced drawings of the treatment group students. This work suggests that iconic features of textbook images may play an essential role in students' understanding of the underlying concepts

1. Liceo scientifico e
delle scienze umane
“Salvatore Cantone”
INVESTIGANTING THE ROLE OF TEXTBOOK IMAGES
ON CHILDREN’S MODELS OF SEASONAL CHANGE
THROUGH FACTOR ANALYSIS OF DRAWINGS
¹ Department of Physics “E. Pancini”, University Federico II, Naples (Italy)
2 Scientific High School “S. Cantone”, Pomigliano D’Arco, Naples (Italy)
3 Physics Division, School of Science and Technology, University of Camerino (Italy)
4 Scientific High School “R. Cartesio”, Giugliano in Campania, Naples (Italy)
5 INAF – Astronomical Observatory of Capodimonte, Naples (Italy)
Testa I.¹, Colantonio A.², Galano S.3
, Leccia S.4
, Puddu E.5

2. Galano & al.
2ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Introduction
• Growing emphasis in science education research on the use of
drawings as effective tool to access students’ reasoning strategies
and mental models (Ainsworth, Prain, & Tytler, 2011)
• Researchers have used drawings as a tool to study pupils’ ability to
give meaning to the depicted representation (Cox, 2005) and to elicit
misconceptions (e.g. Vosniadou & Brewer, 1994)
• Some authors suggested that drawings are products of pictorial
conventions in cultural contexts (Ehrlén, 2008)
• Drawings may be influenced by pictures in school textbooks, which
represent for students a conventional cultural context of visual
representations (Lee, 2010)

3. Galano & al.
3ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Introduction
• However, until now, very little is known about
how textbook pictures affect pupils’ drawings
of a given phenomenon.
• This study addresses this issue choosing
change of season as content.

4. Galano & al.
4ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Research question
To what extent do textbook images influence
students’ drawings about change of seasons?

5. Galano & al.
5ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Theoretical framework
Students’ interpretation of science visual representations
and textbook images
• Knowledge of visual language involves the awareness of semantic and
interpretative processes at the basis of communication through visual
representations (Schnotz, 2002). To know the visual language adopted in
science implies to know how information are encoded in scientific
representations through the representational syntax
• Scientific texts can be considered in general multimodal (Lemke, 1998):
featuring different modes (verbal, mathematical, and visual), interacting
with each other
• Visual representations might foster students’ learning processes since
they preserve geometric and topological relationships with the objects
they represent (Schnotz, 2002)

6. Galano & al.
6ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Theoretical framework
Students’ interpretation of science visual
representations and textbook images
• All the previous studies emphasize that specific support is
needed to take full advantage of visual representations
• When such support is lacking, or when representations are
oversimplified or impoverished, the sole presence of
photographs, drawings, and diagrams in school textbooks
does not guarantee a greater effectiveness in communicating
scientific concepts (Mayer and Sims, 1994; Roth et al., 2005)

7. Theoretical framework
Students’ interpretation of astronomy textbook images
Only few studies have focused
students’ difficulty with the
interpretation of diagrams and
iconic representations of
astronomical phenomena. Most
research studies generically point
out that representations of these
phenomena are often complex or
ambiguous because they are
two-dimensional representations
of phenomena that occur in a
three-dimensional space (Kikas,
1998; Duschl, et al., 2007; Barab et al.
2000; Hansen et al., 2004)
Example of a common Italian text book
(Zanichelli Editore)

8. Galano & al.
8ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Theoretical framework
Students-generated visual representations and
learning in science
●
To involve students in the process of generating drawings
could promote students’ memory, observation, and
imagination (Neu and Berglund, 1991; Stein and Power, 1996)
●
Drawings is a way to select and capture certain features of
the reality in order to construct pattern of reasoning about it
(Cox, 2005)

9. Galano & al.
9ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Methods: sample
373 first-year high school and middle school students
(average age: 13.0 ± 1.1 years)

10. Galano & al.
10ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Treatment Group (N=193) Control Group (N=180)
Methods: design
• short curriculum sequence (1 h) about change of seasons
• three months after having completed the sequence,
participants were randomly assigned to a treatment and a
control group
NO IMAGES

11. Galano & al.
11ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Methods: instruments and analysis
• Written task requesting a drawing and an explanation
• Drawings: exploratory factor analysis (Libarkin at al. 2015)
• Explanations: categorization using the constant comparison
method*
* inter-rater reliability: 0.73
Code Description
Correct
Change of seasons is explained in terms of Earth axis tilt and orbital motion
around the Sun
Partial
Change of seasons is explained in terms of changing incidence of sunrays on
Earth
Distance
Change of seasons is explained mainly in terms of changing distance between
Sun and Earth
Naive Change of seasons is explained mainly in terms of personal experience

12. Galano & al.
12ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Results
Factor analysis of drawings:
• Kaiser-Meyer-Olkin measure of sampling adequacy was
0.759
• Bartlett’s test of sphericity was significant (χ2
(120) = 2310,
p<10-4
)
• Four factors emerged (criterion of eigenvalues ≥1)
explaining 58% of the variance
• 2 more hybrid models from factor loadings and factorial
scores

13. Models emerged
Code Model Model Description
Variance
explained
Frequency
Treatment Control
Earth-Sun
● Earth and Sun
● no orbit is present
● arrows
23% 23% 23%
Rays
● Sun-rays hitting the Earth with
different inclinations
15% 7% 24%
Orbit
● Two or more Earth;
● Orbit with Sun-Earth distance
11% 42% 19%
Axis
● Inclined axis with poles
● Angle
● Sun-Earth distance
9% 17% 9%
Naïve* ● Weather elements - 2% 18%
Hybrid**
● At least two or more elements
of the above emerging models
- 9% 7%
*Model corresponds to conceptual features with a negative factor loading for all factors
** Model assigned to students’ drawing with low factorial score for all factors
χ2
(5) = 63.459, p < 104

14. Galano & al.
14ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Categories of explanations
χ2
(3) = 3.020, p = 0.389
Control Treatment Total
Naive 17 12 29
Distance 83 87 170
Partial 48 48 96
Correct 32 46 78
Total 180 193 373

15. Galano & al.
15ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Models vs explanation
χ2
(15) = 78.014, p < 104
Treatment and Control
Naive Distance Partial Correct Total
Model
Earth-
Sun
3 52 24 6 85
Rays 3 16 14 24 57
Orbit 5 69 27 15 116
Axis 5 11 11 22 48
Clima 8 12 10 5 35
Hybrido 5 10 10 6 31
Total 29 170 96 78 373

16. Galano & al.
16ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Discussion
• Results confirm that students’ drawings are influenced by
contextual factors, as textbook images
• The proposed textbook image led to a distance-based model
• More emphasis on science images’ design, and on the
development of teaching-learning sequences that might help
students correctly interpret textbook images
• Promote the use of Refutation Graphics (Mason et al., 2017) that
are images designed to activate a misconception, refute it,
and present the correct conception
• Development of Innovative images specifically designed to
avoid the reinforce of the most common misconceptions

17. Galano & al.
17ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
Next steps
• How are students’ explanations and visual
representations about familiar astronomy phenomena
affected by different image-support conditions?
• How are students’ conceptions about familiar
astronomy phenomena affected by different image-
support conditions?
• Which iconic elements of the designed innovative
images did affect the most students’ visual
representations and explanations of familiar
astronomy phenomena?

18. Thanks for your attention
silvia.galano@unicam.it

19. Galano & al.
19ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
● S. Ainsworth, V. Prain, and R. Tytler, 2011; Drawing to learn in
science. Science, 333, 1096
● S. A. Barab, K. E., Hay, M. Barnett, and T. Keating, 2000;
Virtual solar system project: Building understanding through
model building. J. of Res. Sc. Teach, 37, 7, 323.
● S. Cox, 2005; Intention and meaning in young children’s
drawing. Int. J. of Art & Des. Ed., 24(2), 115.
● R. A. Duschl, H. A. Schweingruber and A. W. Shouse, 2007;
Taking science to school: Learning and teaching science in
grades K-8. (The National Academies Press, Washington,
DC, 2007).
● K. Ehrlén, 2009; Drawings as Representations of Children's
Conceptions. Int. J. of Sc. Ed., 31(1), 41
References

20. Galano & al.
20ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
● J. A., Hansen, M. Barnett, J. G. MaKinster, and T. Keating,
2004; The impact of three-dimensional computational
modeling on student understanding of astronomy concepts:
a qualitative analysis. Int. J. of Sc. Ed., 26(13) 1555
● E. Kikas, 1998; Pupils’ explanations of seasonal changes: age
differences and the influence of teaching. British J. of Ed.
Psych., 68(4) 505
● V. R. Lee, 2010; Adaptations and Continuities in the Use and
Design of Visual Representations in US Middle School
Science Textbooks. Int. J. of Sc. Ed., 32(8), 1099
● J. L. Lemke, 1998; Multiplying meaning: Visual and verbal
semiotics in scientific text. In J. R. Martin and R. Veel (Eds.),
Reading science: Critical and functional perspectives on
discourses of science (pp. 87–113) (Routledge, London and
New York, 1998)
References

21. Galano & al.
21ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
● J. C. Libarkin, S. R. Thomas and G., 2015; Ording Factor Analysis
of Drawings: Application to college student models of the
greenhouse effect, Int. J. of Sc. Ed., 37(13) 2214.
● L. Mason, R. Baldi, S. Di Ronco, S. Scrimin, R. W. Danielson, G.
M. Sinatra, 2017; Textual and graphical refutations: Effects on
conceptual change learning. Contemporary Educational
Psychology 49, 275–288
● R. E. Mayer, and V. K. Sims, 1994; For whom is a picture worth a
thousand words? Extensions of a dual-coding theory of
multimedia learning. J. of Ed. Psych., 86, 389.
● G. Neu, and R. Berglund, 1991; The disappearance of drawings in
children’s writing: A natural development or a natural disaster?
(Northern Illinois University, DeKalb, 1991)
References

22. Galano & al.
22ESERA CONFERENCE – DUBLIN 21-25 AUGUST 2017
● W.-M. Roth, L. Pozzer-Ardenghi, and J. Y. Han, 2005; Critical
graphicacy: Understanding visual representation practices in
school science. (Springer, Dordrecht, 2005)
● W. Schnotz, 2002; Toward an integrated view of learning from
text and visual displays. Ed. Psych. Rev. 14(1) 101
● M. Stein, and B. Power, 1996; Putting art on the scientist’s
palette. In Hubbard, R. S., and Ernst, K. (eds.), New Entries:
Learning by Writing and Drawing (Heinemann, Portsmouth,
NH, 1996)
● S. Vosniadou and W. F. Brewer, 1994; Mental models of the
day/night cycle. Cogn. Sc., 18, 123.
References