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Empowering K-12 Students With Disabilities to Learn Computational Thinking and Computer Programming



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TEACHING ExcEptional childrEn | SEptEmbEr/octobEr 2015 45
TEACHING Exceptional Children, Vol. 48, No. 1, pp. 45 –53. Copyright 2015 The Author(s). DOI: 10.1177/0040059915594790
Mr. Rose, a third grade general
education teacher, and Ms. Smith,
a special education teacher, co-teach
in an urban elementary school with
a high number of students receiving
free or reduced-price lunch. The school
integrates computer science and
computational thinking into curriculum
as part of their science, technology,
engineering, and mathematics (STEM)
initiative. Mr. Rose and Ms. Smith have
identified several challenges they will
need to address to meet the needs of
several of their students with learning
disabilities. These challenges include
difficulty with complex, multistep
problem solving, lack of access to
and experience with technology, and
difficulty with fine motor skills.
There is an increased focus on
including computing and
computational thinking in K-12
instruction within science, technology,
engineering, and mathematics (STEM)
education and to provide that
instruction in ways that promote access
for students traditionally
underrepresented in the STEM fields,
such as students with disabilities
(Israel, Pearson, Tapia, Wherfel, &
Reese, 2015). Several reasons drive this
focus on computing for a broad range
of learners. First, of all the STEM fields,
the greatest demand for workers exists
in computer science. In fact, the U.S.
Department of Labor has estimated
that there will be 1.4 million job
openings for computing-related jobs by
2020, but at the current rate of people
being prepared for those positions,
only approximately 30% of those
positions will be filled (Bureau of
Labor Statistics, U.S. Department of
Labor, 2014). The National Science
Foundation (2009) explained that
beyond traditional computer science
and programming positions, computing
is becoming necessary in other career
paths including journalism and the
creative arts. Second, (n.d.), a
nonprofit industry aimed at expanding
computing education opportunities in
K-12, has predicted that approximately
two thirds of all computing jobs will be
outside of the technology industry in
areas such as banking, retail,
government, entertainment,
manufacturing, and health care. Thus,
the demand for workers who are
skilled in computing will be across
industries. In addition to the pipeline
rationale, there are several instructional
benefits for students that result from
the inclusion of computing within K-12
programs. These include:
Creating real-world applied contexts
for teaching mathematics,
algorithmic problem solving, and
collaborative inquiry (Fessakis,
Gouli, & Mavroudi, 2013; Jona et al.,
Building higher-order thinking skills
(Kafai & Burke, 2014)
Increasing collaborative problem
solving (Kafai & Burke, 2014)
Increasing positive attitudes about
computer science and computer
science skills (Baytak & Land, 2011;
Lambert & Guiffre, 2009)
Thus, providing computing experiences
for K-12 students with and without
disabilities can open the doors to
multiple career paths and provide
broad educational benefits.
Despite national attention on
computer science, many teachers have
naïve conceptions about what
computational thinking and computing
entails because computing has not yet
been fully integrated into teacher
594790TCXXXX10.1177/0040059915594790Council for Exceptional ChildrenTeaching Exceptional Children
Empowering K–12
Students With Disabilities
to Learn Computational
Thinking and Computer
Maya Israel, Quentin M. Wherfel, Jamie Pearson, Saadeddine Shehab, and Tanya Tapia
Original Article
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46 council for ExcEptional childrEn
There is an increased focus
on including computing
and computational
thinking in K-12
instruction within science,
technology, engineering,
and mathematics (STEM)
education and to provide
that instruction in ways
that promote access for
students traditionally
underrepresented in the
STEM fields.
preparation. To address this confusion,
the Computer Science Teachers
Association and International Society
of Technology in Education (2011)
broadly defined computational thinking
as a “problem-solving process” that
formulating problems in a way that
enables us to use a computer and
other tools to help solve them;
logically organizing and analyzing
data; representing data through
abstractions such as models and
simulations; automating solutions
through algorithmic thinking (a
series of ordered steps); identifying,
analyzing, and implementing
possible solutions with the goal of
achieving the most efficient and
effective combinations of steps and
resources; and generalizing and
transferring this problem solving
process to a wide variety of
problems. (p. 1)
It can be gathered from this definition
that students with disabilities who
struggle with complex problem
solving, mathematics, and abstract
reasoning may face numerous
challenges when presented with
instruction in computing. For
example, students with disabilities
may struggle with abstract computing
processes such as a multistep
procedure for using “if, then”
commands and with new vocabulary
such as algorithm (Israel et al., 2015).
Consequently, the national focus on
increasing computer science and
computing education directly
influences the work of special
educators. Teachers working with
students with disabilities must now
consider how to best support their
learners within these inclusive
educational environments so that
they can meaningfully engage in and
benefit from computing education.
How Is Computing Typically
Taught in K-12 settings?
There are many ways to integrate
computing education into K-12
instruction, and the resources to
support this instruction continue to
grow. Computing education may
involve either linear progression
through discrete computing skills with
tutorial software that teaches
computing (e.g., or the Khan
Academy) or open exploration/inquiry
where students and their teachers use
programming software for their
instructional purposes. Younger
students often begin learning
computing (i.e., how to use a
computer) and programming (i.e., how
to code) with graphically intuitive tile-
based software such as the open-source
software Scratch. Older students may
begin with these same programs or
learn how to program within
professional programming languages
such as Java or Python. Table 1
provides a list of popular computing
and programming curricula used in
K-12 settings, and Figure 1 provides an
example of an elementary student’s
project within Scratch. In addition to
teaching computing in isolation,
computer science instruction can also
be integrated into the content areas,
especially in math and science. For
example, when teaching geometry,
students can program animations for
different polygons. Israel and
colleagues (2015) found that
elementary school teachers often
integrated computing into content area
instruction due to a lack of dedicated
time for computing instruction.
Strategies That Increase
Access and Engagement in
Computing Education
Teaching Computing Through the
UDL Framework
Universal design for learning (UDL) is an
instructional planning framework for
meaningfully engaging a range of
learners, including students with
disabilities, by proactively addressing
barriers to learning (Center for Applied
Special Technology [CAST], 2011; Rose &
Meyer, 2002). There is a growing body of
research demonstrating the educational
efficacy of teaching through the UDL
framework (e.g., Marino et al., 2014;
Rappolt-Schlichtmann et al., 2013).
Within the context of computing
education, UDL can serve as the
instructional framework in which
teachers can embed the necessary
supports, technologies, and strategies
that lead to effective instruction for a
broad range of learners. Table 2
showcases how the UDL principles,
guidelines, and checkpoints can support
accessible computing instruction.
UDL encompasses three central
principles that can be applied to
computing education.
1. Multiple means of representation.
Principle 1 emphasizes that teachers
should present instruction in
multiple ways so that students have
different methods of accessing that
information. During computing
instruction, this principle is critical
as students often benefit from a
variety of different presentation
methods. Depending on their needs,
students can observe the teacher
model the use of computing software
(such as Scratch or Alice), see the
code that the teacher created
afterward, watch videos and demos
of that code used online, or break
apart existing code that their teacher
modeled. For some students a
combination of these engagement
options or variation in sequence of
presentation is required.
2. Multiple methods of action and
expression. Principle 2 emphasizes
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the use of multiple methods for
allowing students to express their
understanding. In computing, this
principle can be achieved fairly
effortlessly because computing
activities inherently have flexibility
built into them. There is not
typically only one way of coding or
demonstrating understanding of that
code. Students can use
programming software in different
ways including creating their own
projects, replicating the teacher’s
program, expanding on the teacher’s
program, or using templates that the
teacher created with partially
created codes. They can also explain
how they designed their program
and provide directions to help peers
replicate their programs.
3. Multiple ways to engage students.
Principle 3 asserts that teachers
should include multiple options for
engaging students. Teachers can do
so by providing choices in computing
projects that involve the same skills
in different way and encouraging
collaboration. It is also important to
include culturally relevant computing
activities such as highlighting careers
of computer scientists with different
cultural backgrounds, genders, and
disabilities and helping students
Table 1. Computing Tools and Curricula
Resource Type and curricular aims
Software; tile-based, open-inquiry programming. Main topics cover both specific
operations and project-based instruction with a primary focus on how to use the
Software; tile-based, open-inquiry programming. It is a 3D programming environment
focused on creating animations and story telling. It is focused on fundamental
programming concepts.
Web site tutorials; basics of programming in a gamified linear “level up” process
of solving increasingly complex puzzles. Topics include fundamental concepts,
JavaScript, unplugged activities, and tutorial apps on a variety of platforms, app
development, and an “other” section.
Khan Academy
Web site tutorials; basics of programming through advanced Java Script, HTML, and
CSS including drawing, games, and simulations. There is also content about computer
science careers.
CS Unplugged
Web site unplugged computing lesson plans; activities that introduce students to
computer science concepts such as binary numbers, algorithms, and data compression
through play with cards, strings, cups, and other manipulatives.
Figure 1. Screenshot of an elementary student’s project in Scratch
Note. Scratch is developed by the Lifelong Kindergarten Group at the MIT Media Lab. See
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48 council for ExcEptional childrEn
make connections between
computing and their own lives.
Teachers can also provide different
learning options. Some students may
prefer “level up” practice within
gamified tutorial programs such as and others may like to
practice those skills in a more open
exploration using software such as
Strategies to consider computing
through the UDL framework are
provided in Table 2.
Balancing Explicit Instruction With
Open-Inquiry Activities
Explicit instruction is a systematic and
direct approach to teaching. This type
of instruction has been demonstrated
as effective for students with learning
disabilities and others who struggle
with following multistep directions
within complex tasks inherent in
computing activities (Israel et al.,
2015). In their book, Archer and
Hughes (2011) researched 16 elements
of explicit instruction illustrating
roughly 30 years of evidence-based
instructional strategies. Table 3 offers
several of these strategies and how
they can be applied for computing
Explicit instruction can reduce
students’ frustrations in computational
tasks because each step is explained
concisely and monitored until students
have mastered the step. Allowing
students ample opportunities to
develop and practice skills that have
been taught is an essential component
of delivering effective instruction. With
that said, it is important to balance
explicit instruction of discrete skills
with open-ended inquiry for students
to have the opportunity to use skills
learned through explicit instruction to
engage in open-ended, problem-solving
computing tasks (Israel et al., 2015;
Kafai & Burke, 2014).
The balance between explicit
instruction and more open computing
instruction can be a challenge for
teachers. Explicit instruction can be
either provided prior to open-inquiry
activities or embedded within those
activities. Israel and colleagues (2015)
described a model wherein teachers
cycled through computing mini-lessons
followed by short periods of open
exploration. Through this process,
teachers provided explicit instruction that
allowed for more successful open inquiry
for students who needed that level of
support. Israel and colleagues described
one teacher, for example, who modeled
how to animate an object in Scratch and
provided step-by-step directions on the
interactive white board. She then had
students use those skills within a
constrained inquiry activity wherein
Table 2. Teaching Computing Through the UDL Framework
Multiple means of representation
Multiple means of action and
expression Multiple means of engagement
Provide options for perception
Model computing using an
interactive whiteboard, videos
Give access to modeled code while
students work independently
Provide access to video tutorials of
computing tasks
Provide options for physical action
Provide teacher’s codes as templates
Include CS Unplugged activities
that show physical relationship of
abstract computing concepts
Use assistive technology including
larger/smaller mice, touch-screen
Provide options for recruiting interest
Give students choices (choose
project, software, topic)
Allow students to make projects
relevant to culture and age
Minimize possible common
“pitfalls” for both computing and
Provide options for language
mathematical expressions, and symbols
Teach and review content specific
Teach and review computing
vocabulary (e.g., code, animations,
computing, algorithm)
Provide options for expression and
Give options of computing software
and materials (e.g., Scratch,, Alice)
Give opportunities to practice
computing skills and content
through projects that build prior
Provide options for sustaining effort
and persistence
Remind students of both computing
and content goals
Provide support or extensions for
students to keep engaged
Encourage peer collaboration by
sharing products
Provide options for comprehension
Activate background knowledge by
making computing tasks interesting
and culturally relevant
State lesson content/computing
Encourage students to ask questions
as comprehension checkpoints
Provide options for executive functions
Guide students to set goals for long-
term projects
Record students’ progress (have
planned checkpoints during lessons
for understanding and progress for
computing skills and content)
Provide options for self-regulation
Communicate clear expectations for
computing tasks, collaboration, and
seeking help
Develop ways for students to self-
assess and reflect on own projects
and those of others
Note. UDL = universal design for learning. For more information on UDL principles, see
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students had choice in what they could
animate but had to use the discrete skills
she modeled. Finally, once the students
demonstrated proficiency in those skills,
they had options for independent
practice within more open computing
activities of their choice.
It should be noted, in computing,
students will know if they used code as
intended based on whether the
inputted code produces the expected
outcome. This is different from other
areas of instruction (such as writing a
grammatically correct paragraph)
because in traditional instruction, the
students may not always know if their
work is correct. Table 3 provides
strategies that account for this inherent
feedback within computing.
Mr. Rose and Ms. Smith are planning
to teach students about the process of
corn and soy production. To integrate
computational thinking with this content
goal, the teachers decide to engage
students in writing programs for a seed to
travel through a food production maze
using Scratch. Ms. Smith suspects that
students with learning disabilities will
struggle with “if, then” codes required to
complete this assignment. She, therefore,
models writing such a code explicitly, and
she leaves her example on the interactive
whiteboard for the students to view as
they create their mazes. Once students
finish writing their codes, they can either
continue to embellish their maze by
adding more features or discuss their
finished product with peers to gain new
perspectives and feedback.
Encouraging Student-to-
Student Collaboration
Computing is often highly collaborative
because of the focus on creativity and
finding solutions to ambiguous or ill-
defined problems. As in other areas of
student collaboration, students with
disabilities and their peers may need to
be taught the necessary skills to work
successfully in collaborative
environments. McMaster and Fuchs
(2002), in their review of collaborative
learning studies, described multiple
training procedures to prepare students
for collaborative learning activities. One
cannot assume that students will know
how to ask a peer for help when
problems occur or that they know how
to offer support to a peer who is
struggling in a manner that promotes
skill acquisition and independence.
Teachers can facilitate these interactions
through cooperative learning strategies.
Computing is often highly
collaborative because of
the focus on creativity and
finding solutions to
ambiguous or ill-defined
problems. Like in other
areas of student
collaboration, students
with disabilities and their
peers may need to be
taught the necessary skills
to work successfully in
Table 3. Explicit Instruction in Computing Education
Select explicit instruction elements within computing
education Examples
Focus instruction on critical content by teaching skills
and concepts associated with the big ideas in computing
Begin lesson with clear goals and expectations and review
prior learning. Provide content and computational goals.
Provide step-by-step demonstrations that break down
complex tasks. Model procedures the way you want the
student to perform the skills.
Use clear and easy-to-understand language that is consistent.
Avoid or clarify terminology that is ambiguous or confusing.
Provide numerous opportunities for guided practice. Provide
more scaffolds in the beginning and reduce scaffolds as
student is mastering the material.
Carefully monitor student performance and use data to
decide when to adjust and intervene to facilitate student
Provide immediate and corrective feedback. Students
recognize errors if their code does not produce expected
Decide which computational skills to teach such as
animating objects.
Give real-world example of the computing tasks in the
lesson to showcase its importance.
Model step by step the code that students will use and do
example on the interactive whiteboard.
When using language such as scripts and coding, provide
definitions and use these consistently in instruction.
Include support during computing time as students try new
scripts and skills. Encourage risk taking and independent
problem solving.
Based on student work and products, teachers note where
students had difficulties to address in the next class.
When students expect code to produce an animation and it
does not, the teacher can ask guiding questions that lead to
correction, provide a scaffold in finding solutions, or model
correct code for the student.
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50 council for ExcEptional childrEn
Cooperative Learning
Cooperative learning involves students
working together to help each other
learn content and discover new
information (Slavin, 1991). It requires
active student involvement and relies
on student interaction as a primary
means for promoting complex
reasoning, critical thought, and the
development of problem-solving skills
(Rose, 2004). It can span across all
grade levels from elementary through
high school and fits well within the
context of computing education. For
example, teachers can form groups and
assign roles for students to program.
Roles could include animation leader,
content leader, coding leader, and
sound effects leader.
Research indicates that successful
cooperative learning is dependent on
individual accountability and group
rewards (Slavin, 1991). Individual
accountability requires each member of
the group to perform an individual task
that contributes to the overall
completion of the assigned group goal
(Johnson & Johnson, 1999). Group
rewards is a form of recognition to all
team members upon the successful
completion of the task. Both factors can
be the incentives for students to actively
participate in cooperative learning.
McMaster and Fuchs (2002) found
that individual accountability and
group rewards have the potential to
increase achievement of students with
learning disabilities. The roles of
students with disabilities should
capitalize on their strengths and allow
for modified expectations if necessary.
For example, if they are collaboratively
creating a game in Scratch, students
who struggle with planning multistep
projects may require preplanning with
the teacher to determine individual
goals prior to the group collaboration.
Student-to-Student Help Seeking
When students cannot find a solution
to a computing problem, they often get
frustrated and want the teacher or
another student to help them find
solutions. To get students to articulate
those problems effectively, studies such
as Webb, Ing, Kersting, and Nemer
(2006) and Karabenick and Dembo
(2011) recommended providing
students with specific prompts to
encourage them “to give elaborated
explanations, to explain materials in
their own words, and to explain why
they believe their answers are correct
or incorrect” (Webb et al., 2006, p. 81).
Accordingly, teachers can encourage
collaborative discourse that provides
students with language to assist them in
seeking and giving help. For example,
Park and Lash’s (2014) collaborative
discussion framework (see Figure 2)
encourages students to collaborate
during computing activities. This
framework guides student conversations
through four questions when they are
stuck on difficult task: (a) What are you
trying to do? (b) What have you tried
already? (c) What else do you think you
can try? And (d) what would happen if
. . . ? (see Figure 2). This framework
should be explicitly taught to students as
a strategy to seek help from other
students before asking the teacher.
Mr. Rose and Ms. Smith encourage
collaborative problem solving in their
classroom. They introduced their
students to the Collaborative Discussion
Framework as a tool that promotes
collaborative problem solving and
reduces learned helplessness and
overreliance on teacher assistance.
Figure 2. Example of Collaborative Discussion Framework classroom
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Students with disabilities use this
framework as a prompt to seek help
from their peers without feeling
embarrassed for not knowing how to
solve the problem.
Experiment With Different
Software and Hardware to
Increase Accessibility
To include a broad range of learners in
computing, teachers should consider
whether the software and hardware that
the students access present barriers to
learning and participation. For example,
students with fine motor difficulties may
struggle with using a mouse. Because of
these barriers, teachers must examine the
accessibility of the hardware and
software their students use.
Assistive technologies (AT) and
instructional technologies (IT) go
hand in hand when considering
access issues during computational
thinking activities. Students with
disabilities who have access to AT
during traditional instruction that
includes technology (such as word
processing) will likely need access to
these technologies during
computational thinking instruction.
The same type of process for making
AT considerations in traditional
instructional areas should be afforded
to computational thinking instruction.
For example, teachers and
individualized education program
teams make AT determination
decisions based on students’ needs
and abilities, the required tasks, and
the learning environment. These same
areas should be considered during
computational thinking instruction.
Ms. Smith observed Thomas, a
student with fine motor difficulty. She
noticed that although he loves engaging
in computer-based learning, he is not
engaged in the planned computing
activity. Upon further observation, she
noticed that he had difficulty with
dragging the coding tiles and making
changes within those tiles. She first
gave him a different mouse to use, but
he still had a difficult time navigating
Scratch. She then allowed Thomas to
use the interactive whiteboard to do his
computing with his hands rather than a
mouse, which was much more effective
for Thomas.
Other tools that teachers can use to
respond to student challenges include
the following:
Fine motor challenges: touch-screen
computers with either different
styluses or using finger gestures,
different size mouses, or the use of
interactive whiteboards
Memory challenges: video tutorials
readily available or video models
created by the teacher, peers, or the
participating students
Complex problem-solving challenges:
experiment with different software
that provide both linear and open
computing activities. For example, and Khan Academy offer
linear lessons, whereas Scratch and
Alice offer a more open platform for
using those skills.
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52 council for ExcEptional childrEn
Final Thoughts
There are many strategies special
educators can employ to increase
opportunities for students with
learning disabilities to succeed in
computing education. Because
computing education is a new area of
instruction, many special educators
may not know how to provide support
to students as they learn computing. In
this article, several strategies and
resources were outlined that special
educators can implement to support
students who find computing
challenging. These instructional
practices should be considered
alongside the individual needs of each
student to develop meaningful,
engaging, and accessible computing
experiences for students with
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Maya Israel, Assistant Professor, Quentin
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Pearson, doctoral student, Saadeddine
Shehab, doctoral student, and Tanya
Tapia, Master’s student, University of
Illinois at Urbana-Champaign.
Address correspondence concerning this
article to Maya Israel, University of Illinois
at Urbana-Champaign, 1310 S. 6th St., 276B
Education Building, Champaign, IL 61820
TEACHING Exceptional Children,
Vol. 48, No. 1, pp. 45–53.
Copyright 2015 The Author(s).
at UNIV OF ILLINOIS URBANA on August 24, 2015tcx.sagepub.comDownloaded from
... It is essential for students to develop deeper knowledge in the field of computer science. Programming courses are generally considered effective in promoting and developing soft skills such as creativity, problem solving, persistence, collaboration, communication and critical thinking [12]. These skills are crucial for a student's future success, given the constant evolution of technology, regardless of their field of study. ...
... These skills are crucial for a student's future success, given the constant evolution of technology, regardless of their field of study. However, programming courses have a negative connotation, there is a widespread opinion among students that programming is difficult [12,13]. ...
Programming is the process of creating and organizing a set of instructions to solve a problem using a computer. In a first phase, we can see programming learning as the acquisition of a set of basic elements of a language. At this stage, this set of elements can be easily memorized. However, for this learning process to be effective, it is necessary to closely monitor each student, focusing on students who begin to manifest difficulties in the first stage of learning. It is important to emphasize that a tutorial action can be performed by people or automated systems. In this work, we present a helping tool to teach and learn to program. Where the plan and activities created by the teacher are privileged. The student has at his disposal a set of exercises framed with the plane defined by the teacher, and practice at his own pace and as often as he deems necessary with the respective immediate feedback.
... Trabajos como los de Bouck & Yadav (2020) muestran actividades e ideas prácticas para integrar en la educación el Pensamiento Computacional, con la intención de la mejora de aprendizaje y habilidades diversas, tales como las matemáticas, en el alumnado con dificultad de aprendizaje. Otros trabajos destacan la importancia de la innovación educativa para acercar y desarrollar las habilidades computacionales en el alumnado con dificultad de aprendizaje, ya que actualmente el 30% de los puestos de trabajos requieren de ciertos conocimientos STEM (Israel et al., 2015). En esta línea, el programa formativo "Música Desenchufada" es un aliado la situación descrita dentro de la educación musical, tal y como se observa en los resultados obtenidos. ...
Resumen. El pensamiento computacional está tomando un papel protagonista en el currículo escolar. En este ámbito, un creciente interés investigador relaciona la mayoría de propuestas educativas con el uso de tecnologías. Este trabajo analiza el desarrollo del Pensamiento Computacional a través de actividades desenchufadas dentro del Área de Música. Un total de 200 escolares de primaria, entre 10 y 12 años (46% chicas, edad M=11.06, DT=1.00), de centros públicos participaron en el estudio. Entre ellos, 150 fueron asignados al grupo cuasi-experimental (45.3% chicas, edad M = 11.08, DT = 1.00) y 50 al grupo control (48% chicas; edad M = 11.00, DT = 1.00). Los datos fueron recogidos en tiempos pre y post – intervención. Computacional Thinking Test fue utilizado para medir el Pensamiento Computacional. El test t-Student fue utilizado para comparar las posibles diferencias entre grupo control y experimental. Modelos de medidas repetidas fueron usados para comparar las diferencias entre la pre y post-intervención, además, se consideró la moderación de las distintas capacidades académicas y del origen étnico-cultural. Los resultados indican que no hay diferencias de medias en el pretest en ninguna variable. Tras la intervención en el grupo cuasi-experimental, los datos señalan un aumento del Pensamiento Computacional en todos los escolares con distintas capacidades académicas, especialmente con el grupo de altas capacidades, y, un desarrollo destacado en escolares inmigrantes y de zonas rurales. Las conclusiones remarcan la posibilidad de plantear estrategias educativas para desarrollar el Pensamiento Computacional, sin usar las tecnologías, y, su eficacia en grupos con distintas características psicosociales.
... This is because computational thinking skills are very important for students, especially vocational schools [45]. Students who have good computational thinking skills will make them smarter, understand technology faster, make students' learning attitudes more optimistic, have the ability to overcome open problems, have perseverance in working through challenges, have resilience in dealing with complex problems, and be able to improve higher-order thinking skills [46], [47]. ...
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span lang="EN-US">Based on the study, computational thinking skills are influenced by science, technology, engineering and mathematics (STEM) skills, and there is a relationship between computational thinking skills and 21st-century skills. However, studies related to STEM attitudes, computational thinking and their impact on 21st-century skills are still very few and limited. The purpose of our study was to examine the impact of STEM attitudes and computational thinking on 21st-century. This research uses a quantitative approach. The participants of this study were students of a vocational school in Bantul Regency, Yogyakarta, Indonesia (N=290). Research data in STEM attitude, computational thinking, and 21st-century skills using a questionnaire. The data were analyzed using structural equation modeling techniques using the Smart PLS application. The results of the study obtained several findings, including: the model proposed in this study was valid; STEM attitude has a positive and significant effect on computational thinking; and computational thinking has a positive and significant effect on 21-st century skills. It can be argued that when STEM attitudes and computational thinking are more positive, 21-st century skills will improve. These findings have implications that curriculum development and STEM learning practices have to develop students’ computational thinking skills and 21st-century skills, especially in vocational schools.</span
... Para el abordaje de la literatura multidisciplinaria sobre la relación entre el pensamiento algorítmico y la resolución de problemas, se aplicó un proceso de revisión sistemática (RS) en educación siguiendo las fases propuestas por Newman y Gough (2020) entre enero de 2015 y junio de 2020, para reunir, sintetizar y evaluar los hallazgos de los estudios que exploran la relación entre las habilidades de PA y las habilidades de resolución de problemas en el contexto de la educación secundaria (Ver figura 2). La revisión de antecedentes permitió corroborar que el pensamiento algorítmico tiene como concepto de base el término algoritmo (Gretter y Yadav, 2016) y está referido, en general, a la creación de un algoritmo como abstracción de un proceso en pasos ordenados (Avello et al., 2020) y que, como solución a un problema puede ser automatizado (Dagienė et al., 2017;Israel et al., 2015;Roldán-Segura et al., 2018;Sánchez Vera, 2019). Como habilidad puede ser detectado cuando los estudiantes son capaces de pensar en términos de secuencias y reglas, ejecutando o creando un algoritmo (Dagienė et al., 2017) tiene aportes cognitivos importantes, especialmente en matemáticas (Palma Suárez y Sarmiento Porras, 2015) y su conexión con situaciones problemáticas de la vida real, a tal punto que se sugiere ser incluido en los planes de estudio de las escuelas (Low y Chew, 2020). ...
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The present research proposes a connection between algorithmic thinking skills and problem solving skills based on a quantitative quasi-experimental study supported by a multiple linear regression model. The results indicate that the applied intervention had statistically significant effects on problem solving skills in the experimental groups and an improvement in the control group; in addition to this, a model equation was determined that predicts the incidence of algorithmic thinking skills on problem solving with a model fit of 47.5% (R2). It is concluded with empirical bases that algorithmic thinking, and the skills that underlie it, decomposition, abstraction and algorithmization, as a didactic strategy in the context of secondary education, has a significant impact on the development of problem-solving skills in students, an issue considered fundamental for the 21st century. La presente investigación propone una conexión entre las habilidades de pensamiento algorítmico y las habilidades de resolución de problemas con base en un estudio cuantitativo cuasi experimental sustentado en un modelo de regresión lineal múltiple. Los resultados indican que la intervención aplicada tuvo efectos estadísticamente significativos en las habilidades de resolución de problemas en los grupos experimentales y una desmejora en el grupo control; adicional a esto, se determinó una ecuación de un modelo que predice la incidencia de las habilidades de pensamiento algorítmico en la resolución de problemas con un ajuste de modelo del 47,5% (R2). Se concluye con bases empíricas que el pensamiento algorítmico, y las habilidades que le subyacen, descomposición, abstracción y algoritmización, como estrategia didáctica en el contexto de la educación secundaria, incide significativamente en el desarrollo de habilidades en los estudiantes para la resolución de problemas, asunto considerado fundamental para el siglo XXI.
... Automatizar soluciones haciendo uso del PA (estableciendo una serie de pasos ordenados para llegar a la solución). Basogain Olabe & Olmedo Parco, 2020; Hacker, 2017;Israel et al., 2015;Sánchez Vera, 2019 Automatizar soluciones mediante el PA (una serie de pasos ordenados). ...
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The curricular structure of mathematics in Colombia establishes problem solving as the general objective of elementary and middle school education. On the other hand, the growing interest in the development of algorithmic thinking in some international curricula, has opened the importance of its reflection for mathematics education. Based on the assertion that algorithmic thinking is a form of problem solving, a systematic review process was applied in education, between January 2015 and June 2020, on the concepts of algorithmic thinking and problem solving. The aim of this article is to present the main findings of the systematic review around how algorithmic thinking skills impact on problem-solving skills in the context of basic secondary education. Of the 66 articles selected, 44 presented considerable contributions to the conceptual configuration of the objective. It was found that the studies established only theoretical relationships between the concepts and no empirical evidence was found that they were established as interdependent variables. Given the latent relationship between algorithmic thinking and computational thinking, the use of the concept of algorithmic thinking in the school educational context is suggested because of its close connection with mathematical knowledge and thinking. In this sense, algorithmic thinking skills can serve as a didactic strategy that contributes to the development of problem-solving skills and thus meet the educational challenge demanded by the 21st century in an increasingly problematized world.
... Barr and Stephenson (2011) emphasised that problem-solving is the core dimension of CT. Problem-solving is interchangeable with CT (Grover & Pea, 2013;Israel et al., 2015). It is the mechanism of seeking any available solutions to confront with daily life problems people are engaging in (Brandell, 2010). ...
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Computational thinking (CT) is defined as a broad spectrum of cognitive abilities including creativity, algorithmic reasoning, critical analysis, problem-solving, collaborative thinking, and communication. There are currently not many self-rated CT skill measurements available. One of these tools for measurement is the Korkmaz Computational Thinking Scale (CTS). The purposes of this present study are to adapt the Korkmaz CTS into Thai and to assess its reliability and validity. Employing a convenience sampling method, data from 3,241 junior high school students in Thailand were collected using Thai translated Korkmaz CTS. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used for data analysis. According to the findings, Thai version of Korkmaz CTS exhibited reliable psychometric properties. However, one item from the Thai CTS was eliminated during the EFA process whereas six items were removed during the CFA. Thus, the Thai CTS can be used as a self-rating instrument to assess the CT of junior high school students in addition to high school and undergraduate students. Schools can measure students' CT faster and with cost-saving.
... Three UDL principles: multiple means engagement, multiple means of representation, and multiple means of action/expression are incorporated into the instructional plans to allow choice and flexibility for all unique learners. UDL has been identified as a promising way to teach computing to students with high-incidence disabilities (Israel et al., 2015) since it allows teachers flexibility to embed the necessary supports and strategies. ...
This article reports results from the implementation of a model of professional development (PD) to help K-5 teachers develop the knowledge and skills to teach Computer Science (CS) in classrooms of diverse students, including students with high-incidence disabilities. This article describes our Inclusive CS model of PD, how we made the PD model available to teachers during a pandemic and presents quantitative and qualitative results about the impact of the PD on teachers’ knowledge, comfort, and beliefs related to teaching computer science to students. Results indicate that the teachers’ knowledge, comfort, beliefs and perceptions about teaching CS to students with disabilities significantly improved. Teachers’ knowledge and understanding of Universal Design for Learning for supporting students in learning about CS also improved.
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Este trabajo tuvo como objetivo realizar una revisión sistemática de publicaciones empíricas acerca de la competencia digital denominada pensamiento computacional en alumnos de nivel secundaria en Iberoamérica en el período comprendido de 2012 a 2022. Para esta revisión sistemática se recopilaron artículos durante los últimos 10 años, se utilizaron bases de datos d acceso abierto, tales como: Google Scholar, Redalyc, Scielo. Adicionalmente, se utilizaron bases de datos académicas de acceso cerrado, tales como: EBSCO, Springer y JSTOR. Se sometieron a criterios de inclusión y exclusión 18 artículos. Se localizaron que la mayoría de los estudios se han realizado en España y entre los principales resultados fueron que la enseñanza de esta habilidad es fundamental para formar estudiantes capacitados en el ámbito de la tecnología lo que a su vez puede mejorar su capacidad para resolver problemas Un aspecto que destaca en esta revisión es el auge de publicaciones en la península Ibérica y la diversidad de temáticas que abordan los autores: resolución de problemas a través de la alfabetización digital e integración en el currículo como asignatura en el nivel secundaria.
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This article examined the performance of 57 students with learning disabilities (LD) from four middle schools. Students were followed over the course of a school year in their inclusive science classrooms as they alternated between the use of traditional curricular materials for some units of study and materials that were supplemented with video games and alternative print-based texts to more closely align with Universal Design for Learning (UDL) guidelines during other units. Findings indicate that video games and supplemental text were effective at providing students with multiple means of representation and expression. The UDL-aligned units led to heightened levels of student engagement. There were no significant differences on posttest scores when students with LD were compared with peers without LD. Students' performance did not indicate significant differences between UDL-aligned units and those taught using traditional curricular materials. Findings suggest a need for alternative assessments to measure learning outcomes during UDL-aligned units. Implications for practice and areas of future research are discussed.
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Science notebooks can play a critical role in activity-based science learning, but the tasks of recording, organizing, analyzing, and interpreting data create barriers that impede science learning for many students. This study (a) assessed in a randomized controlled trial the potential for a web-based science notebook designed using the Universal Design for Learning (UDL) framework to overcome the challenges inherent in traditional science notebooks, (b) explored how teacher characteristics and student use of supports in the digital environment were associated with productive inquiry science learning behaviors, and (c) investigated students' and teachers' perceptions of the key affordances and challenges of the technology to their learning. Use of the UDL science notebook resulted in improved science content learning outcomes (γ = .34, p < .01), as compared with traditional paper-and-pencil science notebooks, and positively impacted student performance to the same degree, regardless of reading and writing proficiency and motivation for science learning at pretest. Students of teachers with greater experience using science notebooks and students who more frequently used the contextual supports within the notebook demonstrated more positive outcomes. Students and teachers reported overall quite positive experiences with the notebook, emphasizing high levels of interest, feelings of competence, and autonomy. (PsycINFO Database Record (c) 2013 APA, all rights reserved). (journal abstract)
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This study employed a case study design (Yin, Case study research, design and methods, 2009) to investigate the processes used by 5th graders to design and develop computer games within the context of their environmental science unit, using the theoretical framework of constructionism. Ten fifth graders designed computer games using Scratch software. The results showed students were able to design functional games, following a learning-by-design process of planning, designing, testing, and sharing. Observations revealed that game design led to opportunities for informal knowledge building and sharing among students. This, in turn, encouraged students to test and improve their designs. The findings support the conclusion that elementary students can develop programming concepts and create computer games when using graphical programming software developed for their level of experience. Insights into the iterative process of learning-by-game design are presented.
Many students are reluctant to seek needed help. In this chapter, we review research on help seeking as a self-regulated learning strategy and describe a set of interventions designed to promote effective use of help seeking.
Computer programming is considered an important competence for the development of higher-order thinking in addition to algorithmic problem solving skills. Its horizontal integration throughout all educational levels is considered worthwhile and attracts the attention of researchers. Towards this direction, an exploratory case study is presented concerning dimensions of problem solving using computer programming by 5–6 years old kindergarten children. After a short introductory experiential game the children were involved in solving a series of analogous computer programming problems, using a Logo-based environment on an Interactive White Board. The intervention was designed as a part of the structured learning activities of the kindergarten which are teacher-guided and are conducted in a whole-class social mode. The observation of the video recording of the intervention along with the analysis of teacher's interview and the researcher's notes allow for a realistic evaluation of the feasibility, the appropriateness and the learning value of integrating computer programming in such a context. The research evidence supports the view that children enjoyed the engaging learning activities and had opportunities to develop mathematical concepts, problem solving and social skills. Interesting results about children learning, difficulties, interactions, problem solving strategies and the teacher's role are reported. The study also provides proposals for the design of future research.
Among educational researchers and practitioners, there is a growing interest in employing computer games for pedagogical purposes. The present research integrated a technology education class and a science class where 5 th graders learned about environmental issues by designing games that involved environmental concepts. The purposes of this study were to investigate how designing computer games affected the development of students' environmental knowledge, programming knowledge, environmental awareness and interest in computers. It also explored the nature of the artifacts developed and the types of knowledge represented therein. A case study (Yin, 2003) was employed within the context of a 5 th grade elementary science classroom. Fifth graders designed computer games about environmental issues to present to 2nd graders by using Scratch software. The analysis of this study was based on multiple data sources: students' pre- and post-test scores on environmental awareness, their environmental knowledge, their interest in computer science, and their game design. Included in the analyses were also data from students' computer games, participant observations, and structured interviews. The results of the study showed that students were able to successfully design functional games that represented their understanding of environment, even though the gain between pre- and post-environmental knowledge test and environmental awareness survey were minimal. The findings indicate that all students were able to use various game characteristics and programming concepts, but their prior experience with the design software affected their representations. The analyses of the interview transcriptions and games show that students improved their programming skills and that they wanted to do similar projects for other subject areas in the future. Observations showed that game design appeared to lead to knowledge-building, interaction and collaboration among students. This, in turn, encouraged students to test and improve their designs. Sharing the games, it was found, has both positive and negative effects on the students' game design process and the representation of students' understandings of the domain subject.