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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, Code.org (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.,
2014)
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
research-article2015
Empowering K–12
Students With Disabilities
to Learn Computational
Thinking and Computer
Programming
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
includes
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., Code.org 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
Scratch
http://scratch.mit.edu/
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
operations.
Alice
http://www.alice.org/index.php
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.
Code.org
http://code.org
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
https://www.khanacademy.org
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
http://csunplugged.org
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 http://scratch.mit.edu.
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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
Code.org and others may like to
practice those skills in a more open
exploration using software such as
Scratch.
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
instruction.
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
devices
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
content
Provide options for language
mathematical expressions, and symbols
Teach and review content specific
vocabulary
Teach and review computing
vocabulary (e.g., code, animations,
computing, algorithm)
Provide options for expression and
communication
Give options of computing software
and materials (e.g., Scratch,
Code.org, Alice)
Give opportunities to practice
computing skills and content
through projects that build prior
lessons
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
goals
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 www.cast.org.
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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
collaborative
environments.
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
education.
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
mastery.
Provide immediate and corrective feedback. Students
recognize errors if their code does not produce expected
results.
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
poster
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TEACHING ExcEptional childrEn | SEptEmbEr/octobEr 2015 51
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,
Code.org 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
disabilities.
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Maya Israel, Assistant Professor, Quentin
M. Wherfel, doctoral student, Jamie
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
(e-mail: misrael@illinois.edu).
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
... Currently, evaluation often relies on subjective observations and interviews with students and instructors (De Araújo and Andrade, 2021). "Explicit instruction" has emerged as a promising approach for teaching IT skills to this population (Israel et al., 2015a(Israel et al., , 2015bSola-Özgüç and Altın, 2022;Baek et al., 2024). This approach involves breaking down complex tasks into smaller, more manageable steps, providing clear demonstrations, offering guided practice, providing immediate feedback to reinforce positive responses and correct negative ones, and promoting generalization of the learned skill to independent use (for a review see Hughes et al., 2017). ...
... The combination of JClic authoring software and explicit instruction proved effective in teaching computer programming skills to individuals with intellectual disabilities. This finding aligns with previous research demonstrating the efficacy of explicit instruction in teaching various skills, including academic skills (Butler et al., 2001;Knight et al., 2012;Bakken et al., 2021;Çapraz, 2023;Rodgers and Loveall, 2023;Schöld et al., 2023;Sulu et al., 2023), also for computer skills (Israel et al., 2015a(Israel et al., , 2015bSola-Özgüç and Altın, 2022). Explicit instruction, which involves breaking down complex tasks into smaller, more manageable steps and providing immediate feedback, is a key component of effective teaching for individuals with intellectual disabilities. ...
Article
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Introduction Teaching computer programming can be challenging, especially for individuals with intellectual disability (ID) who exhibit a wide range of learning abilities and behavioral characteristics. This study aimed to investigate the effectiveness of an intervention designed to teach computer programming skills to individuals with ID. Method Four women with ID, aged 27 to 54 years, were selected to participate in the study. Participants were taught computer programming using authoring software to create multimedia educational activities. A discrete trial teaching (DTT) approach was employed to teach specific skills and to gradually fade prompts to promote independent learning. A multiple-probe design across subjects was used to evaluate the effectiveness of the intervention. This design involved a baseline phase, a training phase with a most-to-least prompting procedure, and a 1-month follow-up phase to assess skill maintenance. Results The results demonstrated that all participants were able to acquire the necessary programming skills and complete the assigned tasks independently. Conclusion Computer programming can provide valuable learning and development opportunities for individuals with ID. However, it is essential to tailor the instruction to individual needs and provide appropriate support.
... We propose there is an additional level currently missing in the literature that describes more technical or production knowledge and skills-the three existing levels consider the digital divide relating to digital use but do not describe knowledge and skills of digital creation. An extension into a fourth level could encapsulate both the skills and benefits of building desktop computers (DiSalvo et al., 2013) or physical computers such as Arduinos (DesPortes & DiSalvo, 2019) as well as learning coding or programming languages (Department for Education, 2018;Guzdial, 2016;Israel et al., 2015). It is this second case that this work seeks to explore, investigating whether this fourth level exists amongst the cohort studied and how prevalent it is. ...
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Digital proficiency, including coding, is increasingly essential in physics education. However, disparities in coding skills among students are influenced by demographic factors and prior educational exposure. This study examines barriers to pre-university coding exposure for first-year physics students across five UK institutions, proposing a fourth level of the digital divide that emphasizes technical and production knowledge in coding. A survey of 199 first-year physics students reveals significant gender and ethnicity differences in coding experience. Males were more than twice as likely to have prior coding experience than females. Students with no prior coding experience viewed it as more challenging, requiring advanced math and powerful computing resources. Despite these challenges, both groups strongly disagreed that gender affects coding ability. Qualitative data pointed to technical difficulties, a lack of role models, and insufficient pre-university exposure as major obstacles. Black, Asian, and Minority Ethnicity (BAME) students reported less teacher encouragement and faced structural barriers similar to those found in literature. The study identifies a fourth level of the digital divide in coding knowledge, stressing the need for targeted interventions to enhance diversity and inclusivity in physics coding education. Recommendations include improving pre-university coding exposure, using gender-sensitive teaching methods, providing consistent encouragement to students, and deeply integrating coding into physics curricula. These steps are vital for preparing students for the digital demands of their academic and professional futures, ensuring equitable access to essential digital competencies.
... Work such as that of Bouck & Yadav (2020) shows practical activities and ideas for integrating computational thinking into education with the intention of improving learning and various skills, such as mathematics, in students with learning difficulties. Other studies highlight the importance of educational innovations to bring and develop computational skills in students with learning difficulties, as currently 30% of jobs require some STEM knowledge (Israel et al., 2015). In this sense, the Unplugged Music training programme is an ally of the situation described within music education, as can be seen from the results obtained. ...
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Working on Computational Thinking in the school environment develops specific skills such as abstraction, algorithmic thinking, automation, among others. In this field, a growing research interest relates most educational proposals to the use of technologies. This paper analyses the development of Computational Thinking through unplugged activities in the field of Music. A total of 200 primary schoolchildren, aged 10-12 years old, from public schools participated in the study. Of these, 150 were allocated to the experimental group and 50 to the control group. Data were collected before and after the intervention. The Computational Thinking Test was used to measure computational thinking. Student's t-test was used to compare possible differences between control and experimental groups. Repeated measures models were used to compare differences between pre-and post-intervention, in addition to considering moderation for different academic abilities, environment and ethno-cultural background. The results indicate that there are no mean differences at pre-test for any of the variables. After the intervention in the experimental group, the data indicate an increase in computational thinking in all students with different academic abilities, especially in the high ability group, and an outstanding development in students with learning difficulties, immigrants, and those from rural areas. The conclusions highlight the possibility of proposing educational strategies to develop computational thinking without using technology, and their effectiveness in groups with different psychosocial characteristics. [es] Desarrollo del Pensamiento Computacional con actividades musicales desenchufadas en distintos contextos educativos Resumen. Trabajar el Pensamiento Computacional en el entorno escolar desarrolla habilidades concretas como la abstracción, el pensamiento algorítmico, automatización, entre otros. 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, de centros públicos participaron en el estudio. Entre ellos, 150 fueron asignados al grupo experimental y 50 al grupo control. Los datos fueron recogidos en tiempos pre y post-intervención. Computational 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, del entorno 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 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 con dificultad de aprendizaje, 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.
... Explicit instruction and open learning were applied during practice sessions. Explicit instruction and open learning are designed to reduce students' frustration in programming tasks and provide ample opportunities to practice the skills they have learned (Israel et al., 2015b). Open learning leverages the advantages of flexible programming activities. ...
Article
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In the digital age, computational thinking (CT)-based problem-solving skills have emerged as essential competencies. Particularly, students with intellectual disabilities need equal educational opportunities and high-quality informatics education to cultivate CT-based problem-solving skills. However, research on the enhancement of CT-based problem-solving skills, specifically among students with intellectual disabilities, is scant. Therefore, this study analyzed the improvement of CT-based problem-solving skills through programming education tailored to students with mild intellectual disabilities in an inclusive educational environment, using evaluation tools that reflect the multidimensional aspects of CT. The study involved 4 students with intellectual disabilities and 9 students without intellectual disabilities.. A customized programming education course, comprising 6 sessions, was designed based on a Universal Design for Learning. Additionally, a pre-posttest consisting of 14 items was developed to evaluate multidimensional CT-based problem-solving skills. The results of the study indicated that the improvement in CT-based problem-solving skills during the stages of problem understanding and algorithm representation was limited. However, significant improvements were observed during the programming and debugging stages among most participants. The findings underscore the necessity of customized programming education for students with intellectual disabilities, and highlight the need for individualized education to address specific challenges faced in programming education. This study is significant in providing foundational data to understand the educational needs and characteristics of these students, aiming to enhance practical applicability in educational settings.
... By integrating robotics into the educational process, ER promotes the active engagement in the learning activity while stimulating autonomy through an interactive, hands on activity (Kight et al, 2019 a-b). This theme addresses not only the cognitive development but also skills such as problem, solving, logical reasoning and sequence planning also in regards to the processes of instruction expression which are of pivotal importance especially for special needs education (Israel et al, 2015). The theme of embedded cognition not only aligns with ER but is a common denominator across all the selected reports since, especially with special needs students, the connection between the physical experience and the learning process allow to reach educational objectives more easily without being hindered by abstract concepts (Oswald et al, 2023). ...
Conference Paper
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The pervasive influence of technology on our lives is calling for a radical shift in the educational curriculum, compelling schools to introduce Computer Science (CS) and Computational Thinking (CT) as essential subjects for today's and future learners. Despite the considerable progress in developing educational content, methodologies, and tools for teaching CS/CT, a notable gap persists in accommodating students with special needs. Within this context, technology is not merely an aid but the actual learning goal. To address this, we conducted a systematic review analysing interventional studies from 2015 to 2024 that involve CS/CT education targeted at students with special needs within the scope of compulsory education. The research questions aim to identify the most successful types of interventions, their benefits, and the overall impact based on the underlying educational approaches. The findings highlight the widespread use of educational robotics as a tool to foster inclusion and engagement among diverse learners. This approach has been shown to improve problem-solving skills and executive functions. Interventions designed for CS/CT education support metacognitive aspects, with tangible interfaces playing a pivotal role in facilitating these processes. Studies targeting specific categories of special needs, such as Autism Spectrum Disorder, have observed a positive impact on social-emotional skills, providing insights for enhancing technology-mediated inclusion in educational settings. Envisioning a future with an increasing number of technology-related jobs, prioritizing CS/CT education for students with special needs could significantly contribute to their future prospects and help them fulfil their potential.
... Inicialmente, foi realizado um estudo da literatura complementado por achados de recursos disponíveis em outros repositórios, tais como plataformas e lojas de jogos digitais. Os trabalhos encontrados evidenciaram plataformas e ferramentas como Scratch 3 , Blocly Games 4 entre outras, através das quais foi promovido o desenvolvimento de competências ligadas ao PC [15,20,28,37]. ...
Conference Paper
Computational Thinking (CT) is a reasoning process focused on solving problems, promoting the development of cognitive skills. Serious games can contribute to exercise these skills, as they are playful and adaptable tools for different audiences. This paper presents the design and evaluation of a medium-fidelity serious digital game prototype designed to help improve the cognitive skills of children with Autism Spectrum Disorder (ASD), based on the fundamental principles of PC. The first phase of the game design was completed and evaluated by Special Education professionals from a partner institution. The observations and feedback collected are being discussed with the development and research teams to implement the functional version of the game.
... More recently, projects and organizations have begun to tackle, through equity focused CS initiatives, other groups that are too frequently excluded from CS, especially students of color (Allen-Handy et al., 2020;DiSalvo et al., 2011). There have also been important initiatives to extend CS instruction to children with special needs (Israel et al., 2015;Ladner et al., 2021). ...
Article
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Over the last decade, there has been an explosion of national interest in computer science (CS) education. In response to this, several organizations and initiatives have emerged in recent years to expand the CS pipeline. However, within these broad and laudable efforts, one important area has been largely overlooked—the instruction of CS to multilingual students, including the large and growing number of students designated as English learners in K-12 schools. These are one of the most underserved and understudied groups in CS education. In this article, we draw on existing research, as well as our own and others’ theoretical and empirical work to date, to put forth both a framework and curriculum for teaching CS to multilingual students.
Article
Over the past few decades, advances in computing power and the widespread adoption of the Internet have completely transformed the ways that people obtain information, communicate, educate, and conduct business. Unfortunately, access to technology and to the training required to use technology are not equitably distributed in the United States, with access much lower in rural areas than urban areas. Further, the urban–rural divide disproportionately affects people in groups that have been historically marginalized in computing, particularly students with disabilities. To address this gap in access and opportunity, we are using Design-Based Research and co-design methods to develop a new technology-based intervention called Furthering Rural Adoption of Computers and Technology through Artistic Lessons (FRACTAL) that incorporates computer science and artificial intelligence into art classes in rural middle schools. In this paper, we describe our co-design process, articulate how and why Design-Based Research and co-design are useful for developing technology-based interventions in schools, and discuss our initial steps to develop FRACTAL in partnership with teachers in rural schools to address the needs of historically disenfranchised and marginalized students.
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Coding education, which enhances the computational thinking skills of K-12 students, is increasingly integrated into the curricula of various countries. However, such education is often excluded from the curricula designed for students with special needs. A review of the literature indicates a significant scarcity of studies dedicated to the coding instruction process for this population. To effectively integrate coding and computational thinking into the curricula for students with special needs, it is essential for educators to understand the appropriate materials and instructional supports that can enhance student motivation and participation during coding lessons. This study aims to evaluate the performance of a secondary school student with mild intellectual disabilities in coding education, with a focus on the materials used, student motivation, challenges encountered during the instruction, and the specific support needs of the student. Employing a holistic single case design, the research incorporates the perspectives of a secondary school special education student regarding their coding education, alongside observations made by the researcher. The findings indicate that the participant actively engaged in the coding education, with block-based coding activities being the most motivating among the various coding activities offered. Furthermore, the study identifies the essential individual supports required by the participant, which include concretization, verbal clarification of the tasks to be performed during each session, and access to the block-based coding platform.
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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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Why every child needs to learn to code: the shift from “computational thinking” to computational participation. Coding, once considered an arcane craft practiced by solitary techies, is now recognized by educators and theorists as a crucial skill, even a new literacy, for all children. Programming is often promoted in K-12 schools as a way to encourage “computational thinking”—which has now become the umbrella term for understanding what computer science has to contribute to reasoning and communicating in an ever-increasingly digital world. In Connected Code, Yasmin Kafai and Quinn Burke argue that although computational thinking represents an excellent starting point, the broader conception of “computational participation” better captures the twenty-first-century reality. Computational participation moves beyond the individual to focus on wider social networks and a DIY culture of digital “making.” Kafai and Burke describe contemporary examples of computational participation: students who code not for the sake of coding but to create games, stories, and animations to share; the emergence of youth programming communities; the practices and ethical challenges of remixing (rather than starting from scratch); and the move beyond stationary screens to programmable toys, tools, and textiles.
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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.
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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.
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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.