Innovative Approaches in Teaching Programming:

A Systematic Literature Review

Simone C. Santos

, Patricia Azevedo Tedesco

, Matheus Borba and Matheus Brito

Centro de informática, UFPE, Rua Jornalista Aníbal Fernandes, s/n, Cidade Universitária (Campus Recife),

CEP: 50.740-560, Recife, PE, Brazil

Keywords: Educational Innovation, Teaching Computer Programming, Systematic Literature Review.

Abstract: One of the main challenges of computing education is the teaching of computer programming. Technical

skills related to algorithm logic, programming language syntax, and computational platforms are required

to program. In addition, several non-technical skills are required, enabling the student to understand and to

interpret real problems, to work in groups and to strive for effective and efficient solutions. To meet these

challenges, innovative teaching methodologies have been applied in teaching programming, building

learning environments that are more conducive to the development of these skills. In order to understand

how these methodologies are being used, this work presents the result of a systematic literature review,

motivated by the following research question: "What are the innovative teaching and learning approaches

to programming, how are they applied and what are the main results of their application? In this study, we

considered three digital libraries and found 24 primary studies, following the Kitchenham methodology.

These studies were categorized into 6 groups and highlighted challenges related to the problems addressed,

teaching environment, content, human capital involved and assessment process. The studies also showed

evidence of success cases, as well as open paths for new research.

1 INTRODUCTION

The evolution of the area of Computing over the last

years is well-known. Computing is everywhere,

whether to make life easier for people or to make

businesses and organizations more efficient and

competitive. It is responsible for automating

processes, maximizing productivity, expanding

communication, enabling better products and

services, allowing the world to be more productive

and agile. In this light, the trend is for this area to

evolve further, requiring qualified professionals to

perform better. This entails that Computing education

follows the evolution of the area, aligning the

academy with the demands of the labor market.

When it comes to computer education, one of the

main challenges is teaching programming. This is

compounded by the need to teach programming

languages and their syntax, that allow instructional

communication with computing machines.

https://orcid.org/0000-0002-7903-9981

https://orcid.org/0000-0001-9450-9219

Programming is not an easy subject. According to

Lahtinen, Ala-Mutka, and Järvinen (2005), learning

programming requires correctly understanding

abstract concepts, mastering the syntax of languages

that often differ from natural language, and logical

reasoning to transform instructions into required

computer actions. Many students experience learning

problems due to the abstract nature of the subject or

lack of enough resources to ensure personal support

from teachers. With regards to group work, there are

also difficulties, many of them concerning the size of

the class versus the size of the teams, the

heterogeneity of the group members, making project

practices where everyone learns difficult.

Consequently, high drop-out rates are often recorded

in programming courses (Lahtinen, Ala-Mutka, and

Järvinen, 2005).

To overcome these challenges, the authors of this

article believe that one of the fundamental

components in improving the quality of teaching

programming is the learning methodology employed.

Santos, S., Tedesco, P., Borba, M. and Brito, M.

Innovative Approaches in Teaching Programming: A Systematic Literature Review.

DOI: 10.5220/0009190502050214

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 205-214

ISBN: 978-989-758-417-6

205

The use of new teaching and learning strategies can

be a way of minimizing the challenges found more

often, attracting more students to the computing area.

In Costelloe (2016), the author defines a number

of approaches for teaching programming, namely: 1)

Lectures & Labs; 2) Software Visualization; 3)

Robots; 4) Problem-Based Learning; 5) Cognitive

Apprenticeship; 6) Miscellaneous. Using these

categories as a key reference, this study defined the

central research question: "CQ - What are the

innovative teaching and learning approaches to

Programming, how are they applied and what are the

main results of their application?".

In order to investigate possible answers to this

question, the Systematic Literature Review (SLR)

method proposed by Kitchenham in (Kitcheham,

2004) was used.

This paper is divided into five sections. After this

brief introduction, Section 2 presents the main

theoretical references used to structure the research

and its analysis. Section 3 describes the application of

the SLR introduced in (Kitcheham, 2004). Section 4

presents and discusses the results found, and finally

Section 5 comments the conclusions and limitations

of this study as well as future works.

2 MAIN THEORETICAL

REFERENCES

Two main references are used to structure this study:

1) different approaches to teaching programming,

according to (Costelloe, 2016) and; 2) a PBL

(Problem Based Learning) methodology used to

organize the report of results found, according to

(Santos, Furtado, and Lins, 2014). We have chosen to

use the Costelloe reference only because it is an in-

depth and detailed study of the main categories of

innovative approaches to teaching programming, and

therefore a source of references in itself.

2.1 The State of the Art of Teaching

Programming

The benefits brought about by recent advances in

research and experience in teaching multilevel

programming show different gains from each

approach used, as well as various uses and impacts of

such approaches. Thus, research has been done to

improve teaching and learning programming. As a

result, Costelloe (2016) presents several approaches

developed, stemming from the technology-driven that

involves the use of visual software, design and

robotics tools to education driven by paradigms such

as PBL and cognitive learning.

According to Costelloe (2016), these approaches

are categorized into six groups: 1) Lectures and labs;

2) Software visualization; 3) Use of robots; 4)

Problem based learning; 5) Cognitive apprenticeship

and; 6) Miscellaneous approaches.

The traditional approach of Lectures and labs

adopts a behavioral theory of learning. The main

applied behavioral theory is operant conditioning,

where the student learns as a result of reinforcement,

whether positive or negative. The students can be

motivated by the teacher's humor, drama, enthusiasm

and knowledge and understanding they acquire.

Software visualization is the practice of mapping

abstract ideas represented in code by visual

representations that make the operation of the system

easier for the observer (Ayrapetov and Graham,

2002). In other words, software visualization is used

to assist the programmer/user of a program to

understand the artifact being observed. In Costelloe

(2016), the author categorizes software visualization

as follows: Programs View, focusing on the graphical

representation of a running program and its data;

Algorithm Animation, testing instructional use and

showing the fundamental operations of an algorithm;

Visual programming, with visual components to

build a program; Demonstration programming, using

Artificial Intelligence programming languages; and

Computational Visualization, viewing statistics, for

example, access points in the code in terms of

counting errors, viewing statistics, for example,

access points in the code in terms of counting errors.

Research shows that active learning, that is,

learning promoted by interaction with the

environment, as opposed to lectures, is more effective

in developing the student's ability to acquire

knowledge (Linder et al., 2001). Linder argues that

active learning can be facilitated by the use of mobile

robots in a collaborative environment. The main

benefits of the use of Robots are (Costelloe, 2016): it

promotes active learning, involving the student and

promoting enthusiasm and fostering the learning

processes; it promotes collaboration and the robot

becomes a participant in this collaboration; it

provides experience with real machines; it promotes

creativity; students can generate hypotheses and test

them by getting feedback immediately; it fosters good

design and planning; it promotes leadership from

practice, which promotes autonomous learning.

The Problem-Based Learning approach (PBL)

concerns a constructivist view of learning, in which

students adjust to existing belief constructs.

According to Costelloe (2016), the main benefits of

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using PBL are: to promote lifelong learning

techniques, forcing the student to reflect about their

learning process and to re-evaluate, through the

maintenance of journals and learning portfolios; to

promote understanding through collaborative work;

to foster learning that driven by problems, rather than

contents, and to be an approach that reflects real-life

problems, preparing students for the job. In such an

approach, problems can range from structured to

poorly structured to meet the needs of beginners and

advanced students. PBL promotes creativity in

obtaining solutions to problems; promotes

independent learning and compels students to take on

responsibility for their work; promotes positive

feelings about the course; and students learn other

skills not specific to course, oral, writing of reports,

demonstration, and critical thinking.

Cognitive apprenticeship is a model of

collaborative teaching where the emphasis is on

supporting the construction of knowledge

(Enkenberg, 2001). According to Enkenberg,

cognitive apprenticeship applies several strategies of

teaching and learning: Modeling, that is, the

demonstration of thought processing; Explanation,

because activities happen as they do; Scaffolding, that

entails supporting students to handle the task at hand,

and gradual withdrawal of teacher from the process;

Reflection, Self-assessment and Self-analysis;

Articulation, which entails reflection results placed in

verbal form; Exploration, where students are

encouraged to form hypotheses, test them and find

new ideas. Similar to PBL, the basic principles of

cognitive apprenticeship relate to constructivism, to

the student constructing their own knowledge, aided

by a specialist initially and gradually becoming an

independent learner, the aspect of collaboration and

the development of metacognitive skills to reflect

about their work.

Finally, these approaches can be combined in order to

help them adapt to specific learning contexts and

obtain diverse benefits from each one. This

combination is pointed out as a "miscellaneous

approach".

2.2 Methodological Elements

This study has used the PBL methodology elements

as a theoretical background for analysing the results

of the SLR. In Santos, Furtado, and Lins (2014), the

authors propose a methodology for the

implementation of PBL in Computing based on 5

manageable elements: 1) Problem, reflecting realism

and complexity similar to real contexts; 2)

Environment, related to the definition of an authentic

learning environment that reflects the actual context

of the professional market; 3) Human Capital, with

evidence to the roles and responsibilities of the

pedagogical team in the planning; 4) Content, as an

essential part to support the theoretical basis of the

problem solving process; and 5) Processes, for the

adequacy of learning objectives and assessment

processes inherent to the learning format in PBL. We

will use these elements as reference in the analysis

described in Section IV, particularly in the results of

question RQ4.

3 RESEARCH METHOD

According to Kitchenham (2004), Systematic

Literature Reviews (SLR) is a method designed to

identify, evaluate and interpret all available research

relevant to a particular research question, area, topic,

or a phenomenon of interest. We guided our

investigation on SLR by the procedures also defined

by Kitchenham. The common reasons for

undertaking a systematic literature review are to

summarise the existing evidence concerning a topic

of interest and to identify any gaps in current research

in order to suggest areas for further investigation.

The individual studies that contribute to a

systematic review are called primary studies; the

systematic review by itself is a form of a secondary

study. The systematic review conducted in this study

was divided into three phases, based on Kitchenham's

guide, namely: Planning the review; Conducting the

review and Reporting the review.

The planning and conducting phases have several

smaller phases, while reporting is a single phase. The

Planning stage can be divided into two main parts.

These can be further detailed as: the Objective of the

systematic review; Development of a review protocol,

that includes the definition of the research questions

(question types; question structure).

The Conducting phase can be divided into five

main parts. Within each one we have more specific

phases, which are: Identification of Research; Study

Selection; Study Quality Assessment; Data

Extraction; Data Synthesis.

This systematic review should answer the

following central question: "CQ - What are the

innovative teaching and learning approaches to

Programming, how are they applied and what are the

main results of this application?". More specifically,

this review focuses on the following issues:

▪ RQ1: What is the teaching context (educational

stage)?

Innovative Approaches in Teaching Programming: A Systematic Literature Review

207

▪ RQ2: What are the innovative approaches of

the studies?

▪ RQ3: What are the main results found from

these approaches?

▪ RQ4: What are the main challenges or

difficulties found in general way?

The initial research studies were conducted using

digital libraries: IEEExplore Digital Library, ACM

Digital Library, and Science Direct. The selection of

these sources was based on the credibility and

relevance of articles indexed in the area of Computer

Science. After selecting our electronic databases, the

search string was created and refined until it was

established and could be used on all bases. By

combining keywords and synonyms the search string

was constructed, as shown:

("teaching" OR "learning") AND ("programming" OR

"programming languages") AND ("innovative" OR

"innovation") AND ("case study" OR "case studies"

OR "lessons learned" OR "experience report")

The research strategy carried out considered

papers published between the years of 2012 and the

first half of 2018 and resulted in a total of 606 papers:

ACM - 65 papers; IEEE - 2 papers; Science Direct -

535 papers;

We established a filter with exclusion criteria. If

the paper fit into at least one, it would be eliminated.

The following exclusion criteria were used:

▪ Exclude artifacts according to the analysis of

titles and abstracts;

▪ Non-English articles;

▪ Articles with paid content;

▪ Duplicate, repeated articles;

▪ Articles not available for download or viewing.

With regards to the last exclusion criterium, we

excluded articles not available for download or

viewing at our institution. In the digital libraries

considered, those often mean articles published in

conference proceedings in recent years. After the

application of this filter, 35 primary studies remained.

Then quality criteria were established; artifacts

that did not refer to the study area or did not present

good content completeness or clarity, or that did not

answer the questions elaborated would be eliminated.

The following are the quality criteria used:

▪ Relevance to the study area/central theme.

▪ Completeness and clarity of contents.

▪ If the study answered the questions.

3.1 Selecting Primary Studies

The initial analysis was based on the introductions

and conclusions of the papers. After the application

of this second filter, 24 papers were obtained. Using

the same quality criteria, we have analyzed the

artifacts by reading them in full: as a result, 20 papers

remained. These papers were the selected works for

extracting the answers and consolidating the results.

The distribution between the databases is found

below:

▪ ACM - 14 papers;

▪ IEEE - 0 papers;

▪ Science Direct: 6 papers.

After the automatic search, a manual search of

papers was performed at conferences that were held

in the second half of 2018. The papers selected went

through all the pre-established steps and we had 4

more papers, all of them were presented in the FIE

2018 (htt://www.fie.org). The total number of papers

selected for analysis is shown in Table 1.

Table 1: Primary studies.

ID Title, Autho

PS1

Perspectives on active learning and

collaboration: JavaWIDE in the classroom

(

Jenkins et al., 2012

)

PS2

CS1001.py: a topic-based introduction to

com

uter science

(

Chor, et al., 2012

)

PS3

Course development through student-faculty

collaboration: a case stud

(

Ustek et al, 2014

)

PS4

Smartphones, Studio-Based Learning, and

Scaffolding: Helping Novices Learn to

Pro

ram

(

Reardon and Tan

, 2014

)

PS5

Teaching Software Engineering with LEGO

Serious Play (Kurkovsky, 2015)

PS6

Teaching Java Programming on Smartphone-

pedagogy and Innovation; Proposal of its

Ontology Oriented Implementation (John

and Rani, 2015

)

PS7

Using Project-Based-Learning in a mobile

application development course—An

experience report (Francese et al., 2015)

PS8

Learning Basic Programming Concepts by

Creating Games with Scratch Programming

Environment

(

Ouahbi et al., 2015

)

PS9

Combining mastery learning with project-

based learning in a first programming course:

an ex

erience re

ort

(

Jaza

eri, 2015

)

PS10

Building Casual Game SDKS for Teaching

CS1/2: A Case Stud

(

Sun

et al., 2016

)

PS11

Using Interactive Exercise in Mobile Devices

to Support Evidence-based Teaching and

Learning (Fuad et al., 2016)

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Table 1: Primary studies (cont.).

ID Title, Autho

PS12

Applying Validated Pedagogy to MOOCs:

An Introductory Programming Course with

Media Computation (Falkner et al., 2016)

PS13

Teaching DevOps and Cloud Computing

using a Cognitive Apprenticeship and Story-

Tellin

roach, Christensen, 2016.

PS14

Visual programming languages integrated

across the curriculum in elementary school:

A two-year case study using “Scratch” in five

schools, Sáez-López et al., 2016.

PS15

Teaching real-time programming using

mobile robots*, Rodrí

uez et al., 2016.

PS16

Computing Curriculum in Middle Schools:

An Ex

erience Re

ort, Sabba

h et al., 2017.

PS17

Computing for Medicine: An Experience

ort

(

Cam

bell et al., 2017

)

PS18

Teaching concurrent and parallel

programming by patterns: An interactive ICT

roach

(

el et al., 2017

)

PS19

K-12 Teachers Experiences with Computing:

A Case Stud

(

Coo

er et al., 2017

)

PS20

Practical Robotics in Computer Science

Using the LEGO NXT: An Experience

Report (Estrada, 2017)

PS21

Applying PBL in Teaching Programming: an

Experience Report (Santos et al., 2018)

PS22

Improving Student’s Learning and

Cooperation Skills Using Coding Dojos (In

the Wild!

)

(

Matheus et al., 2018

)

PS23

Student Experiences with Collaborative

Problem-Based Learning (CPBL) in a

Second-Year Undergraduate Engineering

Course

(

Fan

, 2018

)

PS24

Inclusive Model for the Development and

Evaluation of Accessible Learning Objects

for graduation in Computing: A Case Study

(Mourão and Netto, 2018)

Figure 1 shows the evolution of the studies over

the last seven years (2012-2018). The curve of the

graph of Figure 1 shows a growing trend in recent

years, considering that the automatic search of RSL

did not include the year 2018 in full.

Figure 1: Temporal distribution of primary studies.

3.2 Limitations and Threats to Validity

This study has some limitations, which exist in any

qualitative research. Considering the literature

review, qualitative findings are highly based on

context, and case-dependent. To avoid bias, well-

established research methods with the support of data

extraction artifacts based on a spreadsheet and tags

definition were adopted, besides the direct

participation of two specialists with vast experience

in teaching computing together two undergraduate

students in computer science.

4 RESULTS

The next subsections comment on the research

questions.

4.1 Teaching Context

Out of the 24 studies, the most found context was

undergraduate teaching (16 out of the 24 studies).

Two studies talk about multiprogram teaching, which

evidences the need for programing skills; three talk

about middle to high school programming and two

studies talk about teaching programming for other

courses, such as medicine, administration and

economy. The following quotes evidence some of

these results:

"This study relates a multi-program (high school

summer enrichment courses, and at two- and four-

year colleges), teaching Java Programming; in GA,

USA”. PS1

"This study relates a high school program that

considers teaching; Basic programming concepts;

the study took place at the Abdellah University,

Morocco.” PS8

"This study reports a computing course in the context

of a Medical Doctor Program at the University of

Toronto.” PS 17

Figure 2 shows a summary of the educational

levels considered in the studies and their respective

concentrations.

Innovative Approaches in Teaching Programming: A Systematic Literature Review

209

Figure 2: Educational levels considered in the studies.

We can see that the greatest concentration of studies

is in adult education, particularly in the undergraduate

stage.

4.2 Proposal of Studies

Considering the categories proposed in Costelloe

(2016), the primary studies have shown evidence of

the adoption of four categories: cognitive

apprenticeship, PBL, robots, and approaches that

involved a combination of these proposals, defined as

“miscellaneous”. Figure 3 shows an overview of this

adoption, with a greater number of evidences to the

cognitive apprenticeship and PBL categories.

Figure 3: Proposal categories identified in the studies.

Table 2 summarizes the proposal of each category,

identifying its respective studies.

With regards to languages and approaches, most

studies use Java or Python, or, alternatively a visual

programming approach. Some deal with game-based

learning and some deal with project-based learning.

Most studies deal with collaborative programming

learning. Out of the 24 studies considered, three used

app development as the main proposal; three used

robot programming as their main approach,

particularly with the Lego NXT robot kit. With

respect to individual and collaborative learning, we

list below some evidences of these results:

Table 2: Primary studies per categories.

Category Proposa

Studies

Lectures& Labs No evidence.

Software

Visualization

No evidence.

Robots

Use of the LEGO

technology (serious

play, Mindstorms,

NXT).

PS5, PS9,

PS15, PS20

PBL

Project-based

practices, in order to

develop games,

mobile apps, systems

prototypes, and so on.

PS6, PS7,

PS8, PS14,

PS21, PS23,

PS24

Cognitive

Apprenticeship

Collaborative

learning, technology

support (such as

games, 3D virtual

environment), and

scaffolding used to

understand and

discuss programming

concepts.

PS1, PS2,

PS10, PS12,

PS13, PS16,

PS18

Miscellaneous

All of them combining

PBL and Cognitive

Apprenticeship, and

two of them also

including robots (PS3

and PS9).

PS3, PS4,

PS9, PS11,

PS17, PS22

"How smartphones, studio-based learning, and

extensive scaffolding were used in combination in the

teaching of a freshman Introduction to Programming

course, beginning with the visual programming

environment Scratch and culminating with Java

development for Android smartphones.” PS4

"This paper discusses the use of the LEGO

MINDSTORMS NXT mobile robots for teaching real-

time programming to bachelor’s students. The stable

real-time control of a segway-like robot with a PID

controller is used as case study to demonstrate the

teaching methodology. Ada was used as real-time

programming language.” PS15

4.3 Main Results

This study used the elements of the PBL methodology

as a theoretical basis for the analysis of the results

found from the use of innovative approaches in

programming teaching. Among the results found, we

highlight the 9 categories as shown in Table 3.

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Table 3: Main results from innovative approaches.

Main Results Description Primary Studies

Technical

Skills

Syntax, semantic, core

concepts, computational

thinking, specific

technologies

PS3, PS6, PS9,

PS11, PS14,

PS15, PS16,

PS18, PS20

Soft Skills

Teamwork, oral

communication,

creativity, critical

thinking, problem

solving, management

skills (time, product

quality, requirements),

self-directed

PS3, PS5, PS7,

PS8, PS16,

PS21, PS24

Collaboration

/Cooperation

Collaborative learning,

Peer review

PS3, PS4, PS6,

PS23

Student

satisfaction

Motivation,

engagement, effective

learning, better student

performance, student

confidence, improved

retention

PS1, PS3, PS4,

PS5, PS7, PS8,

PS9, PS10,

PS11, PS12,

PS13, PS14,

PS15, PS16,

PS17, PS18,

PS20, PS21,

PS23, PS24

Real

experiences

Real practices, create

application, thoughts of

entrepreneurship,

sharing experience with

software professionals

PS6, PS14,

PS20, PS22,

PS23, PS24

Content

sharing

Software code, artifacts,

apps, exercises

PS1, PS10,

PS11, PS13

Assessment

Monitoring of the

student progress,

continuous feedbac

PS1, PS7,

PS11, PS21

Ample

curriculum

Curriculum with ample

vision of the CS area

PS2

Teaching

training

Professional

development to in-

service K-12 teachers

PS19

The most discussed results highlighted the

motivation and engagement of students through the

use of innovative teaching approaches and strategies

and intense collaborative work, always with great

enthusiasm and recommendation of continuity of the

respective proposals. The following evidences

illustrate some of these results:

"The resulting course meets goals and objectives,

provides wonderful motivation, and highlights

creativity and intellectual challenge within computer

science as well as syntax, semantics, and core

technical skills.” PS3

"In this pedagogical design, students interact and

create their own content related to curricular areas

with several advantages, such as motivation, fun,

commitment, and enthusiasm, showing improvements

related to computational thinking and computational

practices.” PS14

"This approach has been very efficient and our

application and had a significant engagement of the

participants in the course, considering the results

obtained and the satisfaction of students in learning

programming.” PS21

Other results also highlighted student

performance, pointing to considerable improvements

in the development of both technical skills related to

the knowledge of key elements in programming

(syntax, semantics, basic and advanced concepts,

platforms) and non-technical (professional skills)

related to teamwork, communication, innovation, and

managerial skills:

"That LSP has a positive impact on student learning,

while also improving student engagement with the

course material. Formal data along with written and

informal feedback from students suggests that LSP

helped improve soft skills, such as teamwork and oral

communication.” P5

"The student performance data shows its effectiveness

in increasing student understanding of difficult

concepts and the overall perception of using the

software was very positive.” P11

“Results show that students who studied computing

through Alice ME showed an improvement in their

critical thinking and problem-solving skills.” P16

A special highlight was the construction of a

practice-based learning environment, promoting

more effective learning from real problems and

solutions, as emphasized in following study:

"Outcomes from our experience can be considered

positive: all the students delivered project artifacts on

time, with a good level of quality and completeness

with respect to the established requirements (as

gathered values for software metrics also suggest).

All the students were enthusiastic in developing apps

for smart devices;(…)” P7

In addition to these results, some studies have

highlighted the sharing of content produced by

students, such as software code, documents,

applications, and other artifacts, which are important

in the learning process. It is also important to remark

the importance of monitoring students' progress with

continuous feedback. Two studies highlighted

specific results, one aimed at proposing a broader CS

curriculum, rather than an emphasis on programming

alone; and another, focused on the training of K-12

teachers, with the aim of forming programming skills

in students before higher education.

Finally, despite considering the challenges

encountered in general, it was possible to identify

how common they are in the categories most found in

Table 2.

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211

4.4 Main Challenges

Considering the positive results of innovations in

teaching programming, not all studies have explicitly

commented on the open challenges. Some studies

highlighted improvements in their learning

environments, problems related to teaching

methodology planning, and others commented on the

culture change related to collaborative work. In order

to facilitate the understanding of the mentioned

challenges, we grouped them according to the

elements of the methodology defined in (Santos,

Furtado, and Lins, 2014), commented briefly in

Section 2.2. The main challenges are shown in Table

Table 4: Main challenges in adopting innovative

approaches.

Main

Challenges

Description

Primary

Studies

Problem

Timing considerations, Short

time for practices, Task

planning, Emphasize

programing process and realistic

context, Presence of computing

in medicine

PS5, PS13,

PS15, PS17,

PS22, PS23

Environment

Configuration and Installation of

programming environments,

Maintenance/Evolution of

specialized labs, Cost of

technologies, Scaling up the

course,

PS1, PS3,

PS4, PS18,

PS20

Content

Lack time to learning specific

topics deeply, Didactic materials

elaboration/ preparation,

Complete pattern libraries using

Java, C ++ and C # languages,

Need to specifically scaffold the

integration of concepts

PS2, PS3,

PS12, PS15,

PS21

Human

Capital

Better to strong students than to

weak students, Adopting

faculty's experience and

expertise in application

domains, culture of sharing and

reflective practices, Competition

between students impacting

participation, Team building,

Some students prefer to study

alone

PS7, PS9,

PS10, PS16,

PS21, PS22,

PS23

Assessment

Process

More rigorous evaluation tools,

Accompaniment of the learning

methodology

PS16, PS21

Regarding the Problem element, some studies

have highlighted the need for special care with the

definition of time to perform tasks, which depending

on its complexity, can overwhelm the student, as in

the quote below:

"Timing considerations are extremely important

when planning an LSP activity that is supposed to fit

a single class period. All LSP case studies described

here were designed for 75-minute blocks.” PS5

Still on this element, the importance of problems

arising from a real context, with the possibility of

practical application, as shown in the quote below:

"As DevOps is highly skills-oriented and has strong

requirements on bringing up complex deployment

architectures fast, we have argued in favor of

teaching methods that emphasize programming

process and realistic context as well as using

performant virtualization environments.” PS13

Regarding the Environment, a special highlight is

the need for configuration and installation of

programming environments, maintenance and/or

evolution of specialized labs, and the cost of

technologies, such as robot development kits, as

highlighted in "we are looking at possibilities for

scaling up the course. The current set of robot kits

limits our enrollment to 66 students, adding NXT is

slightly complicated by the fact that the NXT v2.0 has

now been discontinued." PS20

This evolution of environments is also related to

two challenges highlighted: high costs and difficulty

in scaling up the course.

Regarding the Content element, some studies

have highlighted the need to develop better and more

complete teaching materials, including the need for

strategies that can promote the integration of contents

in an easier way for students. Study (Falkner et al.,

2016)

highlights this need:

"These results support a hypothesis of the need to

specifically scaffold the integration of concepts,

beyond their mastery as individual concepts.” PS12

Challenges related to the Human aspect are also

commented on. In (Jazayeri, 2015) the study

emphasizes that the approach favors students who are

stronger over the weaker ones:

"Our combined approach helped the strong students

more than the Finaweak students.” PS9

Although some studies have shown concern about

the formation of teams aiming at collaborative work

(Santos et al., 2018), other studies point to

characteristics that hinder collaboration, such as

competitiveness, making it difficult to share artifacts,

and preference for individualized study:

"students 1) are stuck on a problem due to not

understanding it, 2) lack support from other students

(in terms of efforts and expertise), 3) have not enough

time to solve problems, and 4) prefer to study alone.”

PS23

From the point of view of teachers, the study

performed by Sung, Nash, and Pace (2016)

emphasizes the importance of adopting the

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experience and knowledge of faculty in application

domains.

Lastly, but by no means least, as far as the

assessment process is concerned, although it is a

critical subject in any discussion on education, few

studies have highlighted it as being a challenge. One

study highlighted the importance of a more rigorous

student follow-up process (Sabbagh et al., 2017); and

another study highlighted the need for management

of learning methodology, always aiming for

improvements (Santos et al., 2018).

5 CONCLUSIONS

The evolution of computing in all areas of daily life,

over the last decades is very well documented. This

entails that the teaching of computing also evolves,

and is kept synchronized with the needs of the market.

However, teaching and learning Programming, one of

the core subjects in computing are not easy tasks

(Lahtinen, Ala-Mutka, and Järvinen, 2005). The

authors of this study argue that one key aspect to be

considered is the teaching methodology used. In this

light, this study has set out to investigate what are the

innovative teaching and learning aspects found in the

literature.

To this end, we have carried out a SLR that aimed

at finding out what are the innovative teaching and

learning methods found in the literature, identifying

the educational context, the results and challenges of

their application. The review was executed in three

Computer Science Digital libraries.

Twenty-four primary studies were found in the

literature. Out of those, eighteen reported

investigations concerning undergraduate

programming learning, in response to RQ1. As far as

languages are concerned, most studies deal with Java

or Python. There is also a trend to use apps, robots

programming, and most experiences also are situated,

using either Project-based learning or Problem-based

Learning (RQ2). It is also reported that the intensive

use of collaborative learning, together with the

continuous monitoring of the students’ progress

fostered motivation and engagement and eagerness to

take projects further (RQ3).

Some of the challenges (RQ4) found involve

structuring and scaling up courses, which is related to

better structuring the learning environments

available; lack of time to learn some concepts more

deeply; time demanded in planning the course and

developing appropriate pedagogical materials. In this

respect we have also found reports of difficulties to

integrate teaching and learning resources that are

available on the web. There are also challenges

related to human capital and teamwork. Challenges

related to human capital encompass finding ways to

cater for both the stronger and weaker students; it also

shows the need to integrating the faculty’s expertise

in real world domains in the classroom, promoting

reflective and collaborative practices. There is also a

need for more evaluation tools and monitoring of the

learning methodologies used.

Finally, the authors believe that the categories

presented in this paper present a good starting point

for researchers in the area. In the near future, the

authors intend to focus on the developing and

assessing new methodologies, and that better

assessment of the application of teaching

methodologies is needed.

Starting with studies that combine approaches

such as PBL and cognitive apprenticeship, one of the

research proposals is to define a teaching

methodology to Python programming for high school

students, a gap that was identified. Each year, our

institution promotes this training based on the PBL

approach, during student vacations. The aim is to

motivate students with the area of computing, from

the development of programming skills. To this end,

we will be analyzing the studies focusing on how to

plan and manage all elements of innovative approach

(problem, environment, content, human capital, and

evaluation process).

ACKNOWLEDGEMENTS

The results presented here were developed as part of

joint research groups: N.E.X.T (iNnovative

Educational eXperience in Technology) research

group, with a focus on Computing Education

Research (CER); "PET Informática", a tutorial

education program created by Brazilian government

with the aim of developing standards of quality and

academic excellence, highlighting the articulation of

teaching, research and extension; and i-team. All of

these groups work at “Universidade Federal de

Pernambuco”, Brazil. Many thanks for all involved in

this study.

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