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The Role of Visual Learning in Improving Students’ High-Order Thinking Skills

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Journal of Education and Practice www.iiste.org
ISSN 2222-1735 (Paper) ISSN 2222-288X (Online)
Vol.7, No.24, 2016
115
The Role of Visual Learning in Improving Students’ High-Order
Thinking Skills
Jamal Raiyn
Computer Science Department, Al Qasemi Academic College for Education, Baqa El Gharbia, Israel
Abstract
Various concepts have been introduced to improve students’ analytical thinking skills based on problem based
learning (PBL). This paper introduces a new concept to increase student’s analytical thinking skills based on a
visual learning strategy. Such a strategy has three fundamental components: a teacher, a student, and a learning
process. The role of the teacher includes monitoring the learning process by considering the most productive way
to improve higher-order thinking (HOT) skills.Many studies show that students learn from courses that provide
information in a visual format. We introduce a meaningful learning strategy for the classroom that promotes the
presentation of information in visual formats such as images, diagrams, flowcharts and interactive simulations.
Furthermore, we compared visual and traditional learners based on their HOT skills, which were evaluated using
the SWOT model. Performance analysis shows that visual leaning tools increased the students’ HOT skills.
Keywords: visual learning, PBL, HOT skills
1. Introduction
Various studies report that 75 of all information processed by the brain is derived from visual formats. Furthermore,
visual information is mapped better in students’ minds (Williams, 2009) ). Visual learning is defined as the
assimilation of information from visual formats. Learners understand information better in the classroom when
they see it. Visual information is presented in different formats, such as images, flowcharts, diagrams, video,
simulations, graphs, cartoons, coloring books, slide shows/Powerpoint decks, posters, movies, games, and flash
cards (Rodger et.al. 2009). Teacher can use the above mentioned formats to display large amounts of information
in ways that are easy to understand and help reveal relationships and patterns. Based on various studies, students
remember information better when it is represented both visually and verbally. These strategies help students of
all ages to better manage learning objectives and achieve academic success.
Visual learning also helps students to develop visual thinking, which is a learning style whereby the
learner comes better to understand and retain information better by associating ideas, words and concepts with
images. Visual information is presented through various interactive visual tools, such as information and
communication technologies (e.g., web services), and 2- and 3-D visual environments. This study focuses on
interactive 2-D games, such as Turtle, at different levels for ages between10 and12. The contribution of this
research lies in its assessment of visual thinking skills.
This paper introduces a new teaching method based on visual algorithms, which can be presented in
graphic form. The visual representation of algorithms is useful both for teachers and pupils in their teaching and
learning. Problem-based learning (PBL) leads to the development of higher-order thinking (HOT) skills and
collaborative skills in students. There are two distinct types of HOT skills needed for problem solving: analytical
and creative. Analytical, or logical, thinking skills use critical thinking and help the reasoner select the best
alternative; they consist of ordering, comparing, contrasting, evaluating and selecting. Creative thinking skills are
also needed for problem solving; these consist of problem finding, efficiency, flexibility, originality, and
elaboration. (Hmelo-Silver, 2004; Bednarz, 2011; Cottrell, 2011; Cottrell, 2013). The goal of the proposed
approach is to study the role of a visual learning environment based on information and communication technology,
in improving students’ HOT Skills. In previous research, we worked on the performance of a HOT thinking
assessment through adaptive problem –based learning (PBL) (Raiyn, 2015). In this study, we introduce a PBL
based visual environment.
2. Related Research
This section summarizes studies that use visual learning. The development of visual thinking skills requires
information that is designed for, and supported by visual tools. We define a representation as the substitute for an
argument in a function, understood in the mathematical sense. It is simply a mapping relation. Inputs and current
states are mapped to subsequent states and outputs such as overt behavior. A function stands for a represented
object, and there is always an implied relation to behavior.
Information collected is stored in the human brain (in the hippocampus), which perceives its environment
and stores the information (knowledge base) in place cells. Based on the representation of the stored information
in the hippocampus, the brain creates cognitive maps, and humans act on the environment by using these maps.
Hence, there are various cognitive maps in the brain, and cognitive map management aims to find shortest path
between the source and the target destination based on decision- making theory. Visual information supports
Journal of Education and Practice www.iiste.org
ISSN 2222-1735 (Paper) ISSN 2222-288X (Online)
Vol.7, No.24, 2016
116
human thought processes and maintains log-tern memory.
Rodger et al. (2009) integrated Alice 3-D in Middle school and designed lessons in math, science,
language arts, social studies and technology. Alice is an innovative 3-D visual programming environment. It
enables users to create an interactive game, animations, and videos, and is a teaching tool available for creating
object-oriented programming.
Ben-Ari (2012) introduced programmable interactive media with Scratch to support the development of
computational thinking skills. Wilson at al. (2009 ) introduced games-based learning, such as scratch, and game-
based construction to engage children at the primary level with computer programming concepts. With Scratch,
users can program interactive stories, games, and animations. It helps young people learn to think creatively. Stolee
and Fristoe (2011) used Kodu Game Lab to introduce children to programming in early ages. Kodu is 3-D visual
programming platform. Kodu can be used to teach creativity, problem solving, as well as programming. Ioannidou
A. (2011) used games to support the development of computational thinking skills and to promote increased
opportunities for computer science education in the regular curriculum. Hero et al. (2015) used the visual
programming platform, MIT App, to increase interest and skills in computational practices. A visual programming
platform, MIT App, enables users to create and to design Android apps and games. It can be used in various fields.
The App Inventor platform teaches students how to program mobile apps, and the material is suitable for middle
school, high school, and college courses. Peluso and Sprechini (2012) used Alice to examine the attitudes of high
school students toward computer science; the students expressed their satisfaction with the use of Alice visual
programming.
We conclude that the use of educational visual programming environments such as, Alice, Scratch, Kodu,
and Greenfoot, supports the development of computational thinking includes logical thinking and algorithmic
thinking, and these involve other kind of thought processes, such as reasoning, pattern matching, and recursive
thinking.
Furthermore, these environments introduce primary school children to visual programming concepts. The
most common ones being taught are loops (iteration) and conditional statements that support problem solving,
logical reasoning and systematic thinking
3. Methods
The SWOT model was used in this study to evaluate HOT skills in the heterogeneous classroom by SWOT stands
for strengths, weaknesses, opportunities and threats (see Figure 1). Based on the evaluation of HOT skills using
the SWOT model, we can determine the strengths, and the weaknesses of individual students.
Figure 1: SWOT model
SWOT was used to evaluate a student’s HOT skills and to support interactions between among students
to improve HOT skills in the group. Figure 1 illustrates the combinations of SWOT categories used to design sub-
group for problem solving in the classroom.
Strengths and Weakness (SW): This combination identifies strengths that can reduce weaknesses.
Weakness and Opportunities (WO): This is combination offers alternative ways to prevent weaknesses.
Weaknesses and Threats (WT): The role of teacher is to prevent threats in light of weaknesses.
Strength and Opportunities (SO): This combination is used to find ways to reduce weakness and threats.
The SWOT analysis was drawn from the internal environment of the classroom to determine the strategy
for building sub-groups. According to student’s HOT skills evaluation, we created sub-groups of three students.
Each sub-group consists of three students. In this case we give the students an opportunity to increase his academic
score. In sub-groups the collaboration between groups member is needed and is evaluated.
There were three strategies for creating the sub-groups:
- The assessment of HOT skills.
- Students’ assessments
- Creating of sub-groups with leaders.
A platform for sharing information was established for the teacher to implement visual learning. This
S
trengths
O
pportunities
W
eaknesses
Threats
Journal of Education and Practice www.iiste.org
ISSN 2222-1735 (Paper) ISSN 2222-288X (Online)
Vol.7, No.24, 2016
117
platform provided visual tools and synchronous and asynchronous communication among students, as illustrated
in Figure 2. Students were asked to give a presentation on an issue in computer science, after which their HOT
skills were evaluated through a face-to-face meeting and an oral test on the project submitted.
Figure 2: Visual learning based PBL
3.1 Lesson plan for visual learning
As illustrated in Figure 3, the teacher selected a lesson in visual learning and the . corresponding learning tools for
presenting the visual material. After introducing the selected lesson, the teacher managed a discussion, solicited
question, and fielded student comments, until all goals were addressed. The teacher distributed the visual
assignment. The teacher then analyzed and summarized the students visual HOT learning skills
Figure 3: Visual learning strategy
Figure 4 illustrates the strategies for creating the sub- groups of students in the classroom. We used two
strategies; the first was based on results of the individual HOT skills analyses, the second was based on students’
self-assessment.
Journal of Education and Practice www.iiste.org
ISSN 2222-1735 (Paper) ISSN 2222-288X (Online)
Vol.7, No.24, 2016
118
Figure 4: strategy for creating group
4. Evaluation of the Visual Code Strategy
The evaluation and performance analysis of student’s HOT skills was based on a mapping process, as illustrated
in Figure 5. HOT skills were classified a low (L), medium (M) or high (H). To improve student’s HOT skills, we
created sub-groups, each consisting of students with H-L HOT skills.
Figure 5: Mapping of students HOT skills
The measurement of HOT skills collaboration was done according to leadership strategy. Students with
high HOT skills led the sub-groups. We scored the group leaders collaboration skills with positive a sign (+) if
they could influence at least one of their group members, otherwise, they were evaluated with a negative sign (-).
To motivate the sub-group members to collaborate, we positioned a student with low HOT skills as the leader, and
other sub- group members collaborated with him, or her to improve the leader’s HOT skills as illustrated in Table
1.
Low
Medium
High
Analysis thinking skil ls
Creative th inking s kills
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
Journal of Education and Practice www.iiste.org
ISSN 2222-1735 (Paper) ISSN 2222-288X (Online)
Vol.7, No.24, 2016
119
Table 1: Leadership strategy
Students HOT skills
Position
Collaboration
Group A
S1
H Leader
+
+
-
S2
L Member
+
+
-
S3
L Member
+
- -
Group B
S1
H Member
+
- +
S2
H\M Member
+
- +
S3
L Leader
+
- -
Figure 6a illustrates the students HOT skills for PBL via the traditional learning process. Figure 6b
illustrates the students’ visual HOT skills. It can be seen that the use of visual tools for PBL increased students’
HOT skills comparison with the traditional learning process. Figure 6c compares traditional HOT skills to visual
HOT skills. Figure 6d compares HOT skills in the traditional learning process to the HOT skills in the visual
learning process. Visual learning improved the HOT skills of students. Figure 6c and Figure 6d illustrates the
strong collaboration among group members. This return to SWOT tools was used to diagnose students’ HOT skills
in the initial assessment of individual students.
Figure 6a: Traditional learning environment
Figure 6b: HOT skills in visual learning
0
20
40
60
80
100
selecting ordering comparing contrasting analysis evaluation
Score
HOT Skills
s1 s2 s3 s4 s5 s6 s7
0
20
40
60
80
100
selection ordering comparing evaluation contrasting analysis
Score
HOT Skills
s1 s2 s3 s4 s5 s6 s7
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Figure 6c: Traditional compared to visual learning strategy
Figure 6d: traditional compared to visual learning strategy
Conclusion and future work
This paper introduces a new visual learning strategy and its impact on the development of student’s high-order-
thinking skills, corresponding to analytical thinking. The SWOT model was used to discuss and to evaluate
student’s performance and their ability to make decisions by creating sub-groups of students. Visual learning offers
better results than traditional learning systems. In primary and middle schools, the effects of visual learning on the
development of student’s HOT skills are significant.
In future work we will consider visual reasoning. In a visual learning environment, the learners use their
eyes to collect visual information. Some studies in human cognition show that in human brain, visual information
is stored accordance with its location in the environment, and it is presumed that the location of the spatial cognitive
map is in the hippocampus. Furthermore we will use the visual learning tools in primary school to study the
Attitudes of pupils toward Learning Programming through Visual Interactive Environments.
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Under the Curriculum for Excellence (CfE) in Scotland, newer approaches such as games-based learning and games-based construction are being adopted to motivate and engage students. Construction of computer games is seen by some to be a highly motivational and practical approach at engaging children at Primary Education (PE) level in computer programming concepts. Games-based learning (GBL) and gamesbased construction both suffer from a dearth of empirical evidence supporting their validity as teaching and learning approaches. To address this issue, this paper will present the findings of observational research at PE level using Scratch as a tool to develop computer games using rudimentary programming concepts. A list of criteria will be compiled for reviewing the implementation of each participant to gauge the level of programming proficiency demonstrated. The study will review 29 games from Primary 4 to Primary 7 level and will present the overall results and results for each individual year. This study will contribute to the empirical evidence in gamesbased construction by providing the results of observational research across different levels of PE and will provide pedagogical guidelines for assessing programming ability using a games-based construction approach.
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Educational programming environments such as Microsoft Research's Kodu Game Lab are often used to introduce novices to computer science concepts and programming. Un-like many other educational languages that rely on scripting and Java-like syntax, the Kodu language is entirely event-driven and programming takes the form of 'when – do' clauses. Despite this simplistic programing model, many computer science concepts can be expressed using Kodu. We identify and measure the frequency of these concepts in 346 Kodu programs created by users, and find that most programs exhibit sophistication through the use of complex control flow and boolean logic. Through Kodu's non-traditional lan-guage, we show that users express and explore fundamental computer science concepts.