Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy,

Motivation for Programming Interest

Ella Kokinda

1 a

, Makayla Moster

1 b

, Paige Rodeghero

1 c

and D. Matthew Boyer

2 d

School of Computing, Clemson University, Clemson, SC, U.S.A.

Department of Engineering & Science Education, Clemson University, Clemson, SC, U.S.A.

Keywords:

Informal Learning, Neurodiversity, Self-Efﬁcacy, Coding Camp.

Abstract:

We explore how using Scratch in a three-week game programming camp impacts students’ interests, moti-

vation, and perceived self-efﬁcacy in programming. In this study of high school students, we use pre- and

post-camp surveys to measure interest in STEM and perceived self-efﬁcacy. Additionally, we use a pre- and

post-skills assessment test to understand how informal learning affects campers’ abilities. We found that when

analyzed as a group, self-efﬁcacy and motivation did not statistically change for the campers. However, in-

dividually, campers trended towards increased self-efﬁcacy and motivation in their skills. Our work extends

current research regarding informal learning opportunities for neurodiverse individuals and situates the effec-

tiveness of informal learning for programming and STEM motivation and interest.

1 INTRODUCTION

As technology advances and we search for the lim-

its of what we can accomplish with software devel-

opment and other technical sciences, considering di-

verse perspectives becomes evermore important to

help drive innovation and solve complex problems.

Researchers have called for introducing STEM ed-

ucation at an early age for more long-term interest

in STEM topics and to promote creative and crit-

ical thinking (Bagiati et al., 2010; Campbell and

Speldewinde, 2022). Early software and game devel-

opment exposure often happens through Scratch

, a

browser-based block programming language for game

development. K-12 Scratch programming has shown

to be beneﬁcial for students to develop computa-

tional thinking, code construction, and coding pat-

terns (Fagerlund et al., 2021). Students who were ex-

posed to programming concepts through Scratch at an

early age may also ﬁnd it easier to transition to non-

visual-based programming languages (Armoni et al.,

2015).

As we continue to push for greater participation

numbers in STEM education and earlier introductions

https://orcid.org/0000-0001-6951-6433

https://orcid.org/0000-0002-0661-0550

https://orcid.org/0000-0002-3859-6239

https://orcid.org/0000-0002-4191-260X

https://scratch.mit.edu/about

to STEM concepts, there is a growing need to rec-

ognize that neurodiverse students, those with ADHD,

autism, and other learning needs, have much to of-

fer in higher education and within the STEM ﬁeld as

a whole (Chrysochoou et al., 2022). However, many

of these students often face barriers in their educa-

tional journey that would otherwise enable them to

embrace their strengths (Syharat et al., 2023; Clouder

et al., 2020). Emerging research shows that we need

to move away from traditional pedagogy, leverage and

embrace universal design standards, encourage stu-

dents to focus on their strengths, and encourage di-

vergent thinking (Chrysochoou et al., 2021; Moster

et al., 2022). Using informal learning, project-based

learning, and multi-model instruction methods, this

camp aims to provide students the opportunity to pur-

sue their strengths, encourage divergent thinking, and

allow for the students to learn at their own pace.

Building on previous research, we explore the

positive impacts of informal STEM learning oppor-

tunities through a three-week summer camp. In this

paper, we make several contributions to software en-

gineering education and broaden the understanding of

STEM informal learning by:

• investigating and reporting ﬁndings on the per-

ceived interest and value of informal learning op-

portunities like summer camps

Kokinda, E., Moster, M., Rodeghero, P. and Boyer, D.

Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy, Motivation for Programming Interest.

DOI: 10.5220/0012710400003693

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 16th International Conference on Computer Supported Education (CSEDU 2024) - Volume 2, pages 413-426

ISBN: 978-989-758-697-2; ISSN: 2184-5026

413

• investigating and reporting ﬁndings on campers’

self-efﬁcacy with game development pre- and

post-informal learning opportunity

• discuss the outcomes of a three-week summer

camp and derive recommendations from our key

successes and suggest areas for improvement

Researcher positionality helps frame the work as

a whole and also shape how and why certain research

decisions were made (Secules et al., 2021). As a

research team, we are motivated to understand how

informal learning opportunities impact neurodiverse

individuals, particularly in STEM-forward situations.

All four authors are White, middle-class, and able-

bodied; the ﬁrst three authors are female, and the

last author is male. Two authors identify as neuro-

diverse individuals; all four have had prior experience

working with neurodiverse groups. Our positionali-

ties and personal experiences help shape our research

approach and motivate us to understand how we can

best support individuals like ourselves in STEM.

2 BACKGROUND

In this section, we discuss informal learning opportu-

nities, student self-efﬁcacy, and the use of future time

perspective.

2.1 Informal Learning Opportunities

Informal leaning opportunities, like summer camps,

provide students with more agency and autonomy in

their educational choices and opportunities for pos-

itive teamwork engagement (Furlong, 2012; Jizat,

2021; Heidari et al., 2021). Particularly in STEM ed-

ucation, prior research shows that informal learning

opportunities may increase student interest in STEM

topics and careers, improve self-efﬁcacy in related

areas, and motivate students to explore STEM in a

formal education setting (Nite, 2014; Dailey, 2018;

DiSalvo, 2014; Maiorca et al., 2020). In particular,

computer science or programming focused summer

camps have been shown to be a positive inﬂuence for

high-school students and provide opportunities out-

side of school to interact with STEM professionals

(Lira et al., 2022; Roberts et al., 2018). These op-

portunities afford students invaluable time to develop

necessary skills that could lead to STEM degree re-

tention and relevant employment within their desired

ﬁeld of study (Espinosa, 2011).

Little research has been conducted with regard

to neurodiversity and STEM or programming related

summer camps for high school students. Additionally,

there is little research on informal learning opportu-

nities and neurodiverse students. Our research aims

to explore how a game development summer camp,

an informal learning opportunity, affects neurodiverse

students motivations and interests in STEM, as well

as measure how much they learn about game devel-

opment.

2.2 Motivation and Interest

Research indicates that motivation and interest play

a key role in gaining and retaining student interest in

STEM topics and careers (Saleh et al., 2019). Stu-

dents’ motivation and interest in STEM can be self-

derived, promoted or encouraged by their parents, be-

ing offered STEM classes in school, or through mo-

tivated teachers who provide and encourage a stu-

dents’ growth and interests (Christensen et al., 2015;

Lee et al., 2018; Rafanan et al., 2020). While re-

search shows that a main motivator for STEM inter-

est is student preference, efforts like informal learning

can spark interest in students who may not have self-

derived STEM interests.

2.3 Self-Efﬁcacy

Self-efﬁcacy refers to an individual’s belief in their

ability to successfully perform a speciﬁc task or

achieve a desired outcome (Bandura, 1997). In the

context of computer science education, self-efﬁcacy

relates generally to a person’s beliefs about their abil-

ity to learn and succeed in computer science (Lin

et al., 2013). It plays a signiﬁcant role in shaping

students’ motivation, engagement, and learning out-

comes. Research suggests that self-efﬁcacy can be

inﬂuenced by various factors, such as goal types and

learning environments (Eccles and Wigﬁeld, 2002).

Creating opportunities for students to engage in in-

formal learning experiences can potentially enhance

their self-efﬁcacy in programming skills. In computer

science education, self-efﬁcacy beliefs play a signiﬁ-

cant role in students’ preference for teacher authority

and their overall satisfaction with e-learning experi-

ences (Lin et al., 2013). Furthermore, self-efﬁcacy

has been found to be a strong predictor of engage-

ment and achievement in various learning contexts,

including computer skills, English language learn-

ing, and science education (Pintrich and De Groot,

1990). Studies have shown that students with higher

self-efﬁcacy beliefs are more likely to engage in

learning activities, persist in the face of challenges,

and achieve better learning outcomes (Rosson et al.,

2011).

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2.4 Neurodiversity

Neurodiversity, as deﬁned by Clouder et al., is an um-

brella term encompassing various neurotypes, e.g., in-

dividuals with Dyspraxia, Dyslexia, Attention Deﬁcit

Hyperactivity Disorder (ADHD), Dyscalculia, Autis-

tic Spectrum, or Tourette Syndrome, that deviate

from the norm, i.e., neurotypical (Clouder et al.,

2020). This concept recognizes and celebrates the

inherent differences in the structure and function-

ing of the brain, resulting in neurological varia-

tions (Roy and Jain, 2021). In the context of this

research with neurodivergent learners, neurodiver-

sity matters because it acknowledges and values the

unique strengths and perspectives that neurodiver-

gent individuals bring to the virtual learning envi-

ronment. Rappolt-Schlichtmann et al. advocate for

a strengths-based approach, including Universal De-

sign for Learning

, to support the overall well-being

and development of students with Dyslexia (Rappolt-

Schlichtmann et al., 2018). This approach aligns with

the aim of this study exploring the impact of infor-

mal learning on students’ interests and motivation,

taking into account their neurodivergent traits. By

acknowledging neurodiversity, educators can create

inclusive learning environments that cater to the di-

verse needs of students, including those with autism,

ADHD, dyslexia, and other speciﬁc learning difﬁcul-

ties.

3 METHODOLOGY

In this section, we describe our methodology for how

we examined campers coding skills and interest in

computing including our research questions, camp

design, participant description, and data collection

and analysis processes. We utilized surveys and ob-

servations throughout the camp to explore the impacts

of the summer camp as an informal learning opportu-

nity in the ﬁeld of game development.

3.1 Research Questions

The objective of this research and this camp is to

enhance understanding of how informal learning op-

portunities affect campers’ interest in computing and

perceived self-efﬁcacy in game development, particu-

larly for neurodiverse campers. Therefore, we ask the

following Research Questions (RQs):

: How does participation in a three-week

summer camp utilizing project-based learning

https://udlguidelines.cast.org/

affect campers’ interest in computing?

: How does participation in a three-week

summer camp utilizing project-based learning

affect campers’ self-efﬁcacy in game develop-

ment?

In RQ1, we aim to understand the campers’ in-

terests in various aspects of computing, whether or

not these interests are career driven, and how three

weeks of informal learning may inﬂuence their com-

puting interests. In RQ2, we examine campers’ per-

ceived self-efﬁcacy in game development and com-

puting. Using a self-efﬁcacy scale and a short knowl-

edge pre- and post-assessment of Scratch skills, we

are interested in the impact of the camp on campers’

computing abilities. The research questions along

with their corresponding data are presented in Table

3.2 Camp Design

We strategically developed the design of our summer

camp to facilitate a virtual three-week program con-

ducted through Zoom. Each student was required to

have an adequate computer that could run Zoom and a

web browser simultaneously. The ﬁrst week of camp

focused on getting the campers the correct software

and extensions they need to work collaboratively in

Scratch and teaching the campers basic elements of

game development and how to brainstorm the story of

their own game. On the ﬁrst day of camp before any

instruction, the research team administered both the

initial skills assessment and computing interests sur-

veys. Then, using demonstrations of a premade game

and providing short videos on each concept needed

to build the premade game from the ground up, the

campers built two timing based games throughout the

rest of the ﬁrst week. Campers would check-in with

instructors every few videos to ensure the task was

completed or receive assistance when needed. The

next two weeks, campers were divided into teams of

four to ﬁve and tasked with collaboratively building

a game from the ground up based on their own ideas

and gaining consensus from their teammates. Each

day of the second and third week of camp campers

would work in teams in breakout rooms with instruc-

tors who would call a stand-up meeting every 15 to 20

minutes to ask the campers what they have been work-

ing on, what they may have completed, and what they

plan on working on next. Finally on the last day of

camp before show-casing each teams game, campers

were given the skills assessment and computing in-

terest surveys for a second time. A comprehensive

timeline of the camp is provided in Table 2.

Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy, Motivation for Programming Interest

415

Table 1: Research question methodology table.

Research Question Methods Data Collected Use

RQ1: How does project based

learning in a three-week summer

camp inﬂuence students’ perceived

interest in computing?

Computing Interest Survey

Future Time Perspective (FTP) Survey

Individual student interests in

computing, future time

perspective, and value of learning

game development

Aggregate and analyze students’

pre-and post-surveys for computing

interest. Use FTP to situate if campers

considered a career in computing or

value in a computing related career

RQ2: How does project based

learning in a three-week summer

camp inﬂuence student perceived

self-efﬁcacy in game development?

10 question Scratch skills assessment,

pre- and post-camp self-efﬁcacy survey,

participant observation video transcripts

Individual student self-efﬁcacy

assessments and skill assessments

and memoed observations

Aggregate and analyze campers’

self-efﬁcacy before and after camp,

using the scratch assessment to consider

results from perceived self-efﬁcacy.

Table 2: Camp Instruction Timeline.

Day 1 Welcome session Meet and greet instruc-

tors and campers Initial research surveys

Install and check required materials and

software

Day 2 Technology check for campers Introduc-

tion to game story types Brainstorm in

groups favorite game story types Building

ﬁrst example game

Day 3 First example game continued

Day 4 Building second example game

Day 5 Creating music and sound effects Brain-

storming game ideas

Day 6 Assign teams Team brainstorming

Day 7-12 Game development

Day 13 Game development continued Invited

guest speaker Practice presenting game to

the other campers

Day 14 Final touches on game Practice presenting

Day 15 Re-administer research surveys Game pre-

sentations

3.3 Participants

Per university human-subjects research requirements,

the research team obtained approval from our Insti-

tutional Review Board (IRB) to conduct this study,

and the camp is offered for free for all students par-

ticipating, regardless of participation in the research

study. We obtained participant consent from both

parents and students using IRB-approved forms and

documents. A total of 22 campers participated the

IRB approved research portion of the camp. However,

over the course of three weeks 8 campers dropped out

and one was asked to leave due to conﬂicts with the

camp’s behavior expectations, leaving us with 13 total

campers who participated in all three weeks of camp

and had both parent and camper consent to partici-

pate in the research. The ages of the campers ranged

from 14 to 17 years old, and 12 were male and 1

was female. Four campers were in 9th grade, two in

10th grade, ﬁve in 11th grade, and two were in 12th

grade. All campers resided in the United States and

attended camp remotely from their respective loca-

tions. Six of our thirteen campers indicated at sign up

that they did not have programming experience in the

Table 3: Camper demographics with programming experi-

ence and self-reported career interests at the start of camp.

ID Age Gender Grade Programming Exp. Career Interest

C1 15 Male 9th None Culinary

C2 16 Male 10th Some - C++, Python Computer Science

C3 15 Male 9th None Journalism

C4 16 Male 11th Some - JavaScript, C++ Game Development

C5 16 Male 11th None Game Development

C6 16 Male 9th None Game Development

C7 14 Male 9th Some - Unspeciﬁed Computer Science

C8 17 Male 12th None Game Development

C9 16 Male 11th Some - Python Computer Science

C10 15 Male 10th Some - Scratch, Python Automotive/Robotics

C11 16 Female 12th Some - C++ Zoology

C12 16 Male 11th None Animation

C13 16 Male 11th Some - Unspeciﬁed Game Development

last year or at all, while seven indicated varying levels

of coding experience. Eight campers indicated inter-

est in a software or game development career, while

others had other STEM interests or interests outside

of STEM completely - culinary, journalism, automo-

tive/robotics, animation, and zoology. A visual of

camper demographics can be found in Table 3.

3.4 Data Collection

To collect data, we employed two surveys using using

Qualtrics

and conducted observations of the campers

during camp activities. We used Qualtrics’ built

in ExpertReview system to ensure accessibility and

readability during the survey, as well as breaking out

into small groups with instructors if students needed

assistance during any portion of the survey.

The ﬁrst student survey consisted of researcher-

adapted questions using a 5-point Likert scale on

computing interest and knowledge (National Center

for Women & Information Technology, 2020), self-

efﬁcacy (Tsai et al., 2019), and future time perspec-

tive (Husman et al., 2007; Husman and Shell, 2008)

for computing, art, and music. Questions for this sur-

vey can be found Appendix A. The second student

survey was a 10 question Scratch skills assessment

developed by the research team with inspiration from

skills assessment questions from De Lira et al. and

found in Appendix B (Lira et al., 2022). Skills assess-

ment questions asked campers to look at code blocks

and answer what code blocks would produce, com-

plete code blocks for a speciﬁc outcome, and gen-

https://www.qualtrics.com/

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416

Table 4: Breakdown of skill assessment questions by com-

puting concepts.

Q# Computing Concepts

Q1 Conditionals

User interaction, conditionals,

code interpretation

Conditional, operators,

code interpretation

Q4 Synchronizaiton

Q5 Loops, operators

Q6 Object interaction, conditionals

Q7 Operators

Q8 Debugging

Q9 Debugging

Q10 Object Interaction

eral knowledge of programming concepts. Overall the

Scratch coding skills assessment investigated campers

abilities in conditionals, operators, user interaction,

code interpretation, synchronization, loops, object in-

teraction, and debugging. A full breakdown of ques-

tions and their related concepts can be found in Table

4. We administered both surveys twice - once on the

ﬁrst day of camp, and again on the last day of camp

after three weeks of instruction.

3.5 Analysis

We initiated the analysis by evaluating surveys that

exclusively featured quantitative data. We crafted

questions on a 5-point Likert scale to measure com-

puting interest, self-efﬁcacy, computing knowledge,

and future time perspective, and implemented a point-

based system for skills assessment, awarding one

point for correct answers and zero for incorrect ones.

For the Likert scale questions, each category was iso-

lated and standard statistical tests were run on each

category. Due to our smaller sample size (less than

20), we opted to also use Hedge’s g to estimate our

effect size (NIST, 2017). Additionally, we performed

the Benjamini-Hochburg adjustment for p-values to

account for any false discovery rates (Benjamini and

Hochberg, 1995). Using corrections to paired-sample

t-test results, we improved our statistical understand-

ing of the data.

3.6 Limitations

We acknowledge that several limitations exist in this

study. One limitation is our sample size. Due to the

nature of our study we anticipated a smaller sample

size, but did not anticipate the number of campers to

drop the camp, thus we chose to accommodate our

statistical analyses using Hedge’s g. Second, survey

studies can be limited by response bias. The idea of

taking surveys for our population may not be consid-

ered exciting or fun and take away time from working

on programming. This may result in campers want-

ing to get through the survey quickly or answer in

an uninterested way. We have provided the duration

of each of the surveys administered to accommodate

this. However, given these limitations, we aim to tar-

get transferability of our results for informal STEM

education at the K-12 level for less represented group

rather than generalizability for neurodiverse individu-

als as whole.

4 RESULTS

In this section, we present the results of our pre- and

post-surveys for skills assessment, self-efﬁcacy, and

motivation.

4.1 Skill Assessment Analysis

As part of understanding campers’ perceived self-

efﬁcacy (RQ

), we investigated campers’ actual

Scratch coding skills pre- and post-camp using an

identical 10-question survey. Pre-camp descriptive

statistics for 21 initial campers show that the overall

average score on a 10-question skills assessment was

6.54, and the median score of 7 out of 10 possible

points. The average time to complete the initial skills

assessment was 10.74 minutes, with a median time of

5.7 minutes. Several campers dropped out throughout

the three weeks of camp, leaving us with 13 campers

for the ﬁnal assessment who participated in the initial

assessment. Post-camp descriptive statistics for the

13 campers show an overall average score of 6.84 and

a median score of 7 out of the 10 possible points. The

average time to complete the ﬁnal skills assessment

was 8.69 minutes with a median time of 6.11 min-

utes. Overall, 6 campers (46.2% ) improved their as-

sessment score by 1 point, 5 campers (38.5%) scores

stayed the same, and 2 campers (15.4% ) reduced their

assessment score by 1.

Questions one, three, ﬁve, eight, and nine all saw

improvements from 7 campers who improved their

scores. The two most common questions improved

upon related to conditionals and debugging, questions

one and nine, respectively. Questions two and eight

saw 3 campers answer incorrectly regarding user in-

teraction, conditionals, and code interpretation, ques-

tion two and debugging in question eight. To note,

only one camper improved their score in two areas

while decreasing their score in another.

Using paired sample t-tests, we analyzed the dif-

Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy, Motivation for Programming Interest

417

ference between the pre- and post-camp assessment

for the 13 campers who stayed through the entirety

of camp. We found that the pre-camp assessment

showed an average score of 6.54 with a standard devi-

ation of 0.97, and the post-camp assessment showed

an average score of 6.85 with a standard deviation of

0.90. A descriptive statistics table is found in Table 5.

Skills assessment results indicate no signiﬁcant mean

increase in campers’ skills, t(12) = -1.48, p = 0.08,

BH corrected p > 0.20.

Additionally, we asked campers within the com-

puting interests and self-efﬁcacy survey their per-

ceived conﬁdence in their current abilities and knowl-

edge in various computing areas. Pre-camp con-

ﬁdence in computing knowledge for the thirteen

campers who completed camp averaged to being

somewhat conﬁdent in their abilities, with an average

score of 18.54 out of 35 total conﬁdence points being

completely conﬁdent. Post-camp conﬁdence in com-

puting knowledge improved slightly, with an average

score of 20.6 out of 35 total conﬁdence points. Using

a paired sample t-test, we found no signiﬁcant mean

increase in campers’ perceived conﬁdence in comput-

ing skills, t(12) = -0.82, p > 0.20, BH corrected p >

0.30. These descriptive statistics can be found in Ta-

ble 5.

4.2 Computing Interest and

Self-Efﬁcacy Analysis

As part of understanding campers’ interest in comput-

ing (RQ

), we investigated campers’ interests in what

they wanted to learn in a three-week summer camp,

understanding the campers’ future time perspective,

and perceived self-efﬁcacy of their coding, music, and

art abilities. For the campers who completed all three

weeks of camp, the descriptive statistics are found in

Table 5.

Perceived computing interest pre-camp averaged

to being moderately interested in various computing

topics with an average score of 39.23 out of 65 to-

tal points. Post-camp interest increased slightly and

averaged to moderately interested, with an average

score of 40.31 out of 65 points. Computing interest

group results indicate no signiﬁcant mean increase in

campers’ computing interests, t(12) = -0.21, p > .40,

BH corrected p > 0.40. The largest change in interest

by speciﬁc questions surrounded an increase in inter-

est in computer networking and thinking of new ways

to apply computer science, and found a decrease in

interest in a college degree.

We also asked camp-speciﬁc questions surround-

ing interest in making games, music, art, learning

about college opportunities, and making new friends.

Pre-camp survey for camp-speciﬁc interest averaged

to being moderately to very interested, with an aver-

age score of 24.31 out of 35 total points. Post-camp

survey for camp-speciﬁc learning interests decreased

slightly and averaged to being moderately to very in-

terested with an average score of 23.80 of 35 points.

Camp-speciﬁc computing interest group results in-

dicate no signiﬁcant mean increase in camp-speciﬁc

computing interests, t(12) = 0.25, p > .40, BH cor-

rected p > 0.40. The largest change in interest by

topic was a decrease in interest in learning more about

computer science and software development and in-

creased interest in creating a videogame.

For our research purposes, future time perspec-

tive (FTP) is used to help situate computing inter-

ests and better understand the campers’ outlook on

a career and interest in programming as a whole us-

ing the value sub-scale from FTP literature. The

value sub-scale included 7 questions regarding use

of the information gained in the camp, skills or con-

cepts learned in camp being used in future projects or

class work, and the importance to campers of under-

standing computing concepts. Pre-camp FTP value

averaged to moderate agreement in having positive

value to the campers’ future with an average of 26.80

out of 35 total points. Post-camp FTP value stayed

about the same, with a marginal decrease with an

average of 26.46 out of 35 total points. FTP value

group results indicate no signiﬁcant mean increase

in campers’ value of what they will learn within the

camp being useful in the future, t(12) = 0.17, p > .40,

BH corrected p > 0.40. The largest change in FTP

value for campers was an increase in believing they

would use information from the camp in the future

and a decrease in believing what was learned in camp

to be important for career success.

To understand campers’ perceived capabilities

with programming, we asked computing-speciﬁc self-

efﬁcacy questions to the campers. Pre-camp student

self-efﬁcacy scores averaged to being somewhat con-

ﬁdent that they had the capabilities to program or un-

derstand certain programming concepts, with an aver-

age score of 48.62 out of 80 total points. Post-camp

student self-efﬁcacy scores increased their belief in

programming capabilities, with an average score of

57.23 out of 80 total points. Computing self-efﬁcacy

group results indicate no signiﬁcant mean increase in

camp-speciﬁc computing interests, t(12) = 0.25, p =

0.09, BH corrected p > 0.20. The largest change

in self-efﬁcacy surrounded the ability to edit and re-

vise programs in an editor, not needing others’ help

to solve a problem, opening and saving code in an

editor, and running and testing code in an editor.

The least amount of change seen in self-efﬁcacy sur-

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418

rounded knowing that work can be subdivided into

smaller tasks, predicting the outcome of code with

logical conditions, and learning more about program-

ming through debugging.

Finally, to understand campers’ perceived capabil-

ities with art and music, we asked music composition

and art creation self-efﬁcacy questions to the campers.

Pre-camp student art and music self-efﬁcacy averaged

to being somewhat conﬁdent that they had the capa-

bilities to make music and art for their games with an

average score of 47.69 out of 80 total points. Post-

camp student art and music self-efﬁcacy scores in-

creased slightly to 53.84 out of 80 total points. Art

and music self-efﬁcacy group results indicate no sig-

niﬁcant mean increase, t(12) = 0.25, p = 0.01, BH cor-

rected p = 0.08. The largest change in self-efﬁcacy for

art and music surrounded an increase in understand-

ing the basic elements of digital animation and draw-

ing in Scratch and understanding the basic elements

of digital music creation.

4.3 Individual Student Results

We analyzed each student before and after three

weeks of camp to understand where their skills, self-

efﬁcacy, and motivation were. Analyzing each stu-

dent individually helps to guide where aspects of the

camp impacted the campers the most and if those im-

pacts reﬂect changes we need to make or aspects to

keep in the camp. Table 6 includes campers with their

respective differences in scores in all survey sections.

C1, male, age 15, no programming experience and

with a career interest in the culinary ﬁeld, saw the

largest increase in his computing interest scores with

a positive change of 17 points. C1 also saw slight

increases in camp-speciﬁc computing interests, com-

puting knowledge, FTP, and self-efﬁcacy (both gen-

eral and art/music categories). He had no change in

his skills assessment.

C2, male, age 16, some programming experience

in C++ and Python, and a career interest in computer

science, saw the largest increase in computing knowl-

edge scores with a positive change of 12 points. C2

also saw small increases in FTP and self-efﬁcacy for

music/art. C2 saw a signiﬁcant decrease in general

self-efﬁcacy with a decrease of 11 points. Addition-

ally, C2 had decreased scores in both general and

camp-speciﬁc computing interests. He had no change

in his skills assessment. The team observed that C2

had an interest in music composition and other music-

related interests that he shared with the team.

C3, male, age 15, no programming experience and

with a career interest in journalism, saw the largest in-

crease in his self-efﬁcacy scores with 17 points in art/-

music and 11 points in general self-efﬁcacy. C3 saw

small a small increase in his camp-speciﬁc computing

interest scores. Additionally, saw the largest decrease

in FTP scores, decreasing by 9 points. C3 also de-

creased scores in general computing interest and com-

puting knowledge, both by one point each. He had an

increase of 1 point in his skills assessment. The team

observed that this student often had some conﬁdence

issues and would be hesitant to speak up unless called

on, but toward the end of camp, he shared more about

what he was working on even when facing issues with

the collaboration software the team used to facilitate

collaboration.

C4, male, aged 16, some programming experience

in C++ and JavaScript, and a career interest in game

development, saw the largest increase in scores with

a positive change of 3 points in FTP. C4 saw some

decrease in scores in general computing interest by 7

points, and a decrease in self-efﬁcacy by three points.

He saw no net change in camp-speciﬁc computing in-

terests, computing knowledge, art/music self-efﬁcacy,

or in the skills assessment.

C5, male, age 16, no programming experience,

and a career interest in game development, saw sig-

niﬁcant increases in his general self-efﬁcacy with a

positive increase of 23 points and in computing inter-

est with positive 22 points. C5 saw small increases

in art/music self-efﬁcacy by 8 points, in computing

knowledge by 6 points, and camp-speciﬁc computing

interests by 3 points. He had no change in FTP and

decreased his skills assessment by 1.

C6, male, age, 16, no programming experience,

and a career interest in game development, saw sig-

niﬁcant increases across the board with positive 58

points in self-efﬁcacy, 31 points in computing inter-

est, 19 points in computing knowledge, 17 in art/mu-

sic self-efﬁcacy, and 14 points in camp-speciﬁc com-

puting interests. C6 saw a decrease of 3 points in FTP.

He also saw an increase of 1 point in his skills assess-

ment.

C7, male, age 14, some programming experience

reported but unspeciﬁed, and a career interest in com-

puter science, saw signiﬁcant decreases in all sections

of the survey except for the skills assessment with no

change. C7 decreased by 27 points in general comput-

ing interests, 17 points in camp-speciﬁc computing

interests, 16 points in computing knowledge, three in

FTP, 18 points in self-efﬁcacy, and 10 pints in art/mu-

sic self-efﬁcacy.

C8, male, age 17, no programming experience,

and a career interest in game development, saw the

largest increase in his general self-efﬁcacy score with

an increase of 14 points. C8 also saw an increase

in his camp-speciﬁc computing interests with an in-

Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy, Motivation for Programming Interest

419

Table 5: Descriptive statistics for thirteen (13) campers with Hedges’ correction to Cohen’s d, Benjamini-Hochberg (BH)

adjusted p-values for self-reported computing interest, perceived self-efﬁcacy in computing, music, and art, perceived com-

puting knowledge, future time perspective.

Pre-Camp Post-Camp

Section Mean SD Mean SD Cohen’s d Hedges’ g p-value BH p-value

Skills Assessment

6.54 0.97 6.85 0.90 -0.41 -0.38 0.08 0.21

Computing knowledge

18.53 8.03 20.62 7.24 -0.23 -0.21 0.22 0.35

Computing Interest

39.23 13.68 40.31 12.11 -0.06 -0.06 0.42 0.42

Computing interest - camp

speciﬁc concepts

24.31 5.94 23.80 5.70 0.07 0.07 0.40 0.42

FTP Value

26.80 6.07 26.46 5.13 0.05 0.04 0.44 0.44

Self-efﬁcacy 48.62 18.15 57.23 11.10 -0.40 -0.37 0.09 0.21

Self-efﬁcacy art + music

47.69 7.78 53.84 7.05 -0.73 -0.69 0.01 0.08

crease of 7 points. He saw a decrease in both com-

puting knowledge and computing interest by 5 and 4

points. He saw no difference in FTP. Additionally, C8

increased his skills assessment by 1. C8 was observed

to be very quiet, but diligently working when given a

task, and typically needed no extra guidance or inter-

vention when working.

C9, male, age 16, some programming experience

in Python, and a career interest in computer science,

saw the largest increase in art/music self-efﬁcacy with

a positive change of 17 points. C9 also saw an in-

crease in FTP scores by 7 points. He saw decreases in

computing interest by 14 points, camp-speciﬁc com-

puting interest by 8 points, self-efﬁcacy by 5 points,

and in the skills assessment by 1 point. He saw no

change in FTP scores.

C10, male, age 15, some programming experi-

ence in Scratch and Python, and a career interest in

automotive engineering or robotics, saw the largest

increase in art/music self-efﬁcacy with a positive

change of 14 points, followed by an increase in gen-

eral self-efﬁcacy by 8 points. C10 also saw small in-

creases in FTP by 5 points, computing knowledge by

3 points, and camp-speciﬁc computing interests by 1

point. He had a decrease in computing interest scores

by 5 points. Additionally, he increased his skills as-

sessment score by 1 point.

C11, female, age 16, some programming experi-

ence in C++, and a career interest in Zoology, saw the

largest increase in general computing interest with a

positive change of 11 points. C11 also increased her

FTP and general self-efﬁcacy scores by 9 points each,

computing knowledge by 6 points, and skills assess-

ment by 1 point. She saw a decrease in camp-speciﬁc

computing interests by 4 points. C11, towards the

end of the camp, increasingly ran into issues and bugs

with the software the camp used to facilitate collabo-

ration.

C12, male, age 16, no prior programming expe-

rience, and a career interest in animation, saw the

largest increase in self-efﬁcacy with a positive change

of 39 points. C12 also increased scores in comput-

ing interest with a 22 point increase, in computing

computing with a 9 point increase, and in the skills

assessment test by 1 point. He saw a slight decrease

in camp-speciﬁc computing knowledge and FTP, both

decreasing by 2 points. C12 had no change in art/mu-

sic self-efﬁcacy.

C13, male, age 16, some programming experi-

ence reported but not speciﬁed, and a career interest

in game development, saw his only score increase in

art/music self-efﬁcacy with a positive score increase

of 9 points. C13 saw decreases in all other categories

by 23 points in computing interest, one point in camp-

speciﬁc computing interests, 10 points in computing

knowledge, four points in FTP, and 16 in self-efﬁcacy.

He saw no change in his skills assessment.

Of campers who indicated that they had no prior

programming experience in the last year - C1, C3,

C5, C6, C8, and C12 - all saw score improvements

in general self-efﬁcacy. C1, C3, C5, C6, and C8 also

all saw improvements in art and music self-efﬁcacy,

while C12 saw no change. C3, C6, C8, and C12

also improved on their Scratch skills assessment af-

ter three weeks of camp. C1 saw no change in their

skill assessment, and C5 had a decrease of one.

In total, 5 of 13 campers saw a positive change

in general computing interests, and 7 saw no change

or positive change in camp-speciﬁc computing inter-

ests. Computing knowledge saw 9 of 13 campers

have no change or positive change to their scores. Fu-

ture time perspective (FTP) saw 8 of 18 campers have

no change or positive change to their scores. Gen-

eral self-efﬁcacy saw 8 of 13 campers have a positive

change to their score and art/music self-efﬁcacy saw

the majority, 12 of 13 campers, have no change or

positive change to their scores. The skills assessment

saw 6 campers with a positive change, 5 campers with

no change, and 2 with negative change.

CSEDU 2024 - 16th International Conference on Computer Supported Education

420

Table 6: Individual student differences between pre- and

post-surveys for each section where CI is computing inter-

est, CI-C is camp-speciﬁc computing interests, CK is com-

puting knowledge, FTP is future time perspective, SE is

general self-efﬁcacy, SE-A/M is art/music self-efﬁcacy, and

Skills is the skills assessment test.

ID CI

∆

CI-C

∆

FTP

∆

SE-A/M

∆

Skills

∆

C1 17 2 4 5 3 2 0

C2 -8 -7 12 5 -11 5 0

C3 -1 5 -1 -9 11 17 1

C4 -7 0 0 3 -3 0 0

C5 22 3 6 0 23 8 -1

C6 31 14 19 -3 58 17 1

C7 -27 -17 -16 -3 -18 -10 0

C8 -4 7 -5 0 14 1 1

C9 -14 -8 0 7 -5 17 -1

C10 -5 1 3 5 8 14 1

C11 11 -4 6 9 9 0 1

C12 22 -2 9 -2 39 0 1

C13 -23 -1 -10 -4 -16 9 0

5 DISCUSSION

In this paper, we posed two research questions aim-

ing to understand how project-based learning in a vir-

tual summer camp can inﬂuence high school-aged

students’ interests (RQ

) and perceived self-efﬁcacy

(RQ

) in computing topics. In the following sections,

we discuss the impacts of the camp on both of our

research questions and give recommendations for oth-

ers who may be interested in similar informal learning

opportunities for K-12 students.

5.1 Promoting Interest in Computing

According to our survey on future time perspective

and computing interests, there was no signiﬁcant

change in the campers’ perceptions or valuation of

a computing career following their participation in

the camp. While this result is surprising, we might

be able to attribute the lack of increased interest in

computing to using a block-based programming lan-

guage. The campers had a wide range of computing

skills, with about half of the campers having expe-

rience in text-based programming languages, which

might have attributed to the lack of change in com-

puting interest and value. Additionally, the camp’s

daily duration of two hours may not have been sufﬁ-

cient enough to promote and practice various aspects

of software and game development.

5.2 Promoting Student Self-Efﬁcacy

Individually, more than half of the campers (8) im-

proved on their general self-efﬁcacy scores, but as

a group, this did not achieve statistical signiﬁcance.

More than half of the campers (9) improved on their

art and music self-efﬁcacy, but as a group with cor-

rections for a small sample size did not make signif-

icance. For the research team, this result was a lit-

tle unexpected, but for those with prior programming

experience, using Scratch could not have been engag-

ing enough or too easy for them. Interestingly, all

campers who did not indicate any prior programming

experience improved on their general self-efﬁcacy,

and three with some programming knowledge also

improved. This leads us to believe that for those

with little to no programming experience, the camp

was successful, in part, at increasing general self-

efﬁcacy through informal project-based learning ac-

tivities. However, for campers with prior program-

ming experience, our camp design may need to be

more engaging or complex to engage the campers in

ways that they felt were worth the effort to participate.

As a research team with prior programming experi-

ence in various programming languages like Python,

C++, and Java, we note that Scratch proved difﬁcult

to work in coming from a non-block-based language.

We speculate that campers with text-based language

knowledge and proﬁciency may also have had a dif-

ﬁcult time translating programming concepts to a

block-based language and led to lower self-efﬁcacy.

5.3 Recommendations

Considering the lack of statistical difference and rela-

tively high pre- and post-skills assessment scores, we

must consider whether Scratch or block-based pro-

gramming is appropriate for high school students.

While many campers indicated that they did not have

any experience with programming in the last year,

block-based languages like Scratch may have been

part of their school curriculum in previous years. Us-

ing Scratch in the way that we did also may have lead

to some of our retention issues with campers through-

out the camp. This leads us to our ﬁrst recommenda-

tion for building an informal STEM summer camp:

Recommendation: Clearly specify the target

programming experience level for the camp.

Little to no change in motivation or self-efﬁcacy

could stem from several causes - lack of feedback,

unfamiliar environment, and/or needing more time in

teams to form a productive team dynamic. Initially,

the research team wanted to focus on having stand-

up meetings every 15 minutes when campers were in

teams working on their ﬁnal game. However, adher-

ing to such a quick turnaround time proved challeng-

ing for teams who had campers who needed extra as-

sistance, were actively working through an issue or

Informal Learning Opportunities: Neurodiversity, Self-Efﬁcacy, Motivation for Programming Interest

421

bug with an instructor or teammate, or instructors did

not want to interrupt campers who were focused on

a task. We felt if campers had a better way to pro-

vide feedback to one another that motivation and self-

efﬁcacy could be increased through positive peer in-

teractions. From this, we give another recommenda-

tion to provide multiple ways to provide feedback.

Recommendation: Provide multiple ways to get

inter-team feedback and facilitate peer-to-peer

review.

Building a repertoire amongst teammates with

positive peer feedback could also alleviate the

campers’ being in an unfamiliar environment. On-

line classes have been shown to be challenging envi-

ronments for campers to form relationships in where

campers may not be able to express themselves fully

with only text or limited amount of camera use

(Symeonides and Childs, 2015). While we facilitate

various ice breakers and social games, the online na-

ture of the camp does not afford itself to quick fa-

miliarly with instructors and other campers. To com-

bat this, the team implemented a Discord server for

campers to utilize during and outside of camp as a

way to facilitate discussions and making connections

with the other campers. Discord was chosen as it is

a popular application for its use in gaming and as a

main communication app for many campers. From

this, we recommend ﬁnding ways to encourage con-

versation between campers in ways that they would

ﬁnd familiar:

Recommendation: Provide the campers with a

familiar way to engage with others.

Along the same vein with having the ability to

form working and familiar relationships, the amount

of time we spend in camp may not have been adequate

enough to begin forming useful or beneﬁcial relation-

ships. This could be increasing the duration of camp

each day. Thus, we recommend re-assessing engage-

ment time with campers each day:

Recommendation: Ensure enough time is allo-

cated in camp to let campers familiarize them-

selves with other campers and staff.

Additionally, increased time in camp could afford

ﬁnding ways to interact with campers in small groups

to get to know each other more. While the research

team used introductions on the ﬁrst day, random-

ized small-group brainstorming, and having campers

move from group to group while making example

games, the campers did not have a signiﬁcant amount

of time dedicated to getting to know one another.

Adding additional time overall to camp and providing

more interactive opportunities could prove beneﬁcial

to campers forming teams naturally rather than camp

staff trying to pair campers together based on inter-

ests and observed interactions. Therefore, to facilitate

more natural teaming, we recommend:

Recommendation: Integrate more “ice-

breakers” and other team-building exercises

into the camp to build repertoire and familiarity

between campers.

Finally, we recommend bringing in speakers who

might be similar or relatable to the campers. In our

camp, we brought in a neurodiverse software and

game developer to speak to the campers about how

they navigated school, their job, and their well-being.

Campers responded well to our speaker with lively

engagement and had many questions after his presen-

tation. Therefore, to give the campers an opportunity

to interface with a mentor-like and relatable ﬁgure, we

recommend:

Recommendation: Invite guest speakers who

are similar to your campers to promote represen-

tation and inspire the campers.

6 CONCLUSION

In this paper, we highlight where informal learn-

ing can be used in K-12 STEM education using a

Scratch-based game development summer camp de-

signed for neurodiverse high school students. Us-

ing surveys and in-situ observations, we found that

campers trended toward increased self-efﬁcacy with

programming skills and increased motivation to pe-

ruse a STEM related topic. We then discuss recom-

mendations for others looking to implement online

informal learning opportunities and recommendations

on providing an environment that encourages and fa-

cilitates low-stakes learning in a collaborative setting.

Through subsequent research we aim to provide ad-

ditional insights into implementing our own recom-

mendations as well as continuing to investigate self-

efﬁcacy and motivation as a result of informal learn-

ing in a summer camp setting.

CSEDU 2024 - 16th International Conference on Computer Supported Education

422

7 DATA AVAILABILITY

For replicability, we have included both an appendix

in this paper and an online appendix of both our pre-

and post-surveys. The in paper appendix includes all

questions related to computing interest and knowl-

edge, future time perspective, and self-efﬁcacy. The

online appendix includes all questions and related im-

ages for the Scratch skills assessment.

ACKNOWLEDGEMENTS

We would like to thank all of the campers who par-

ticipated this year, it was amazing to see the amount

of creativity and determination everyone had to make

their game ideas come to life.

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APPENDIX

Appendix: Survey Questions

Computing Interest

Regardless of whether or not you have actually tried

it, how interested are you in:

Making computers more intelligent (more like

people)

Creating algorithms to make computers faster

Understanding how computers present data and

images

Designing computer games

Computer networking (like the internet)

Thinking of new ways to apply computer science

(like new apps or games)

Programming computers to create new apps

Finding technological solutions to world problems

using computer science

How much do you want to:

Take a computer science class

Take a game development class

Get a college degree

Get a computer science or technology related col-

lege

degree

Get a computing related career as an adult

Computing Interest - Camp Speciﬁc

During camp, how interested are you in:

Learning to code a videogame

Learning to make music

Learning to make art

Learning about college opportunities

Learning more about computer science and soft-

ware

development

Making friends

Learning something you don’t know

Computing Knowledge

Right now, how conﬁdent are you in your ability to:

Learn computer science concepts

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Make computers more intelligent (more like peo-

ple)

Think of new ways to apply computer science

Find technological solutions to world problems

using computer science?

Design computer games

Understand how computers present data and im-

ages

Create algorithms to make computers faster?

Future Time Perspective

Please respond to the following:

One shouldn’t think too much about the future

It is important to have goals for where ones to be

in 5-10 years

One should be taking steps today to help realize

future goals

I don’t think too much about the future

I don’t like to plan for the future

Its not really important to have future goals for

where I want to be 5-10 years

Planning for the future is a waste of time

I have been thinking about about what I want to

do in the future

It is no use worrying about the future

What will happen in the future is an important

consideration in deciding what to do right now

What might happen in the long run should not be

a considerations in making decisions right now

What I do today will have little impact on what

happens 10 years from now

Half a year seems like a long time to me

I need to feel rushed before I can work on some-

thing

I always Seem to do things at the last moment

I ﬁnd it hard to get things done without a deadline

In general, six months seems like a very short pe-

riod of time

I will use the information I learn at this camp in

the future

I will use the information I learn in this camp in

other classes or projects in the future

What I learn in this camp will be important for my

career success

I will not use what I learn in this camp at all

Having an understanding of software and game

development is valuable

Understanding software and game development is

important to me

What I learn in this camp will be important for

personal success

General Self-Efﬁcacy

Please answer the following questions about your pro-

gramming ability:

I can understand the basic logical structure of a

program

I can understand a condition expression such as

”if...else...”

I can predict the ﬁnal result of a program with log-

ical conditions

I can predict the result of a program when given

its input values

I know programming work can be divided into

sub-tasks for people

I can work with others while writing a program

I can make use of divisions to enhance program-

ming efﬁciency

I can ﬁgure out program procedures without a

sample or example

I don’t need others help to construct a program

I can make use of programming to solve a problem

I can open and save a program in a program editor

I can edit and revise a program in a program editor

I can run and test a program in a program editor

I can ﬁnd the origin of an error whole testing a

program

I can ﬁx an error while testing a program

I can learn more about programming during the

debugging process

Self-Efﬁcacy Art and Music

Please answer the following questions about your dig-

ital art and music abilities

I understand the basic elements of digital drawing

I understand the basic elements of digital anima-

tion

I understand the basic elements of digital drawing

in Scratch

I understand the basic elements of digital anima-

tion in Scratch

I am conﬁdent I can draw and animate characters

for a game

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425

I am conﬁdent I can draw and animate background

scenes for a game

I understand the basic elements of digital music

creation

I understand the basic elements of digital music

creation in scratch

I am conﬁdent that I can successfully make music

for elements of a game

Appendix: Skills Assessment Questions

The skills assessment and its accompanying images

can be found via an online appendix:

https://ﬁgshare.com/s/972dc1457358a0d161f2.

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