Literature review of recent trends and innovations in teaching first year introductory CS course presented during Faculty Development Program at JIIT (6-11 July, 2015)

1. TRENDS AND
INNOVATIONS IN FIRST
CS COURSE
-Aayushee Gupta

2. Outline
 Curriculum Guidelines from ACM IEEE 2013
Report
 Survey of curriculum, techniques, languages
and environment used
 Teaching pedagogies
 Flipped Classroom
 Peer instruction
 Pair Programming
 Visualization based programming
 Problem Posing

3. Curriculum Guidelines from
ACM IEEE 2013 Report
 SDF (SOFTWARE DEVELOPMENT FUNDAMENTALS) : This new KA
generalizes introductory programming to focus on more of the software
development process, identifying concepts and skills that should be
mastered in the first year of a computer-science program
 The new KA also provides students with a view of software beyond
programming skills, including topics from Algorithms and Complexity (e.g.,
basic analysis, fundamental data structures), Software Engineering (e.g.,
small scale reviews, basic development tools), and Programming
Languages (e.g., paradigm-independent constructs).

4.  DESIGN CONSIDERATIONS
 Providing multiple pathways into and through introductory course
sequences can make computer science more accessible to different
audiences
 Care must be taken to emphasize the more general concepts in computing
within the context of learning how to program
 A programming-focused introductory course can help develop essential
skills in students early on. Too narrow a programming focus in an
introductory class, while giving immediate facility in a programming
language, can also give students a too-narrow (and misleading) view of the
place of programming in the field
 The inclusion of software development practices in introductory courses
can help students develop important aspects of real-world software
development early on
 The use of specific platforms can bring compelling real-world contexts into
the classroom and platforms designed for pedagogy can have beneficial
focus

5. Survey Paper -1
 AIM: To identify trends in student numbers, programming language and
environment/tool use and the reasons for choice of these, paradigms
taught, instructor experience, text used and time spent on problem solving
strategies in lectures and tutorials and compare with previous censuses
conducted during 2001 and 2003
 MATERIALS: Study of 44 introductory programming courses in 28
Australian universities, conducted in the latter months of 2010.
 EXPERIMENTAL PROCEDURE
 Audio-recording of phone interview of around 10 to 15 minutes duration
with administrative or academic staff responsible
 Questions were asked regarding the language and paradigm choice,
teaching duration, instructor experience, textbooks, problem solving
strategies and development tools, mental effort required to understand and
learn aspects of programming using the language(s) used in each course
Mason, R., Cooper, G., & de Raadt, M. (2012, January). Trends in introductory programming
courses in Australian universities: languages, environments and pedagogy. In Proceedings of the
Fourteenth Australasian Computing Education Conference-Volume 123 (pp. 33-42). Australian

6.  FINDINGS
 Average numbers of enrolments per course have halved, falling from 349 in
2001 to just 176 in 2010
 Languages taught in Australian universities continue to be dominated by
Java
 Languages that are seen as particularly beneficial for learning purposes
(rather than for industry use) are becoming more popular, such as Python,
Alice and Processing
 Few courses that introduced novice users to three or more languages
 Choice of programming language and environment is governed by
pedagogical reasons
 The focus on the object-oriented paradigm and the objects-first approach to
learning programming appears to have reduced since the 2003 census

7. Language comparison by
percentage of courses
Number of languages taught in a course
Hours in class on-campus
Reasons for language choice

8. Trends in environment use
Trends in paradigms taught
Levels of mental effort

9. Survey Paper -2
 AIM: Survey the languages and techniques taught in CS0,CS1 and CS2
courses across 371 undergraduate computer science schools in the U.S.,
quantifying which practices are actually in common use
 EXPERIMENTAL PROCEDURE
 Selected every 10th and 5th school majoring in CS course from Carnegie
Classification List and US News University Directory respectively and sent
online surveys to 785 institutions
 Survey included questions on languages, environments, programming
paradigms, interactive debuggers and time spent on teaching programming
and algorithms skills in CS0,CS1 and CS2 courses
Davies, S., Polack-Wahl, J. A., & Anewalt, K. (2011, March). A snapshot of current practices in
teaching the introductory programming sequence. InProceedings of the 42nd ACM technical
symposium on Computer science education (pp. 625-630). ACM

10.  FINDINGS
 Over one-third of schools don't regularly offer a CS0 course at all, and
those that do use an enormous variety of languages, and spend a widely
differing amount of class time on programming vs. other topics
 CS1 and CS2, by contrast, are far more uniform across schools.
 Alice is by far the most common novice-focused environment in common
use; while Java and C++ more dominant in CS1 and CS2 courses
 70.6% of schools (262/371) teach CS1 and CS2 in the same language.
 Interactive debuggers are used in 228 (61.5%) of CS1 courses, and 244
(65.8%) of CS2 courses.
Types of development environments used.

11. The most popular languages used in CS0
courses.
Percentage of CS0 class time spent
“teaching algorithmic and programming
The most popular languages used in CS1
and CS2.
Percentage of respondents who indicated
that the “object-oriented programming
paradigm” was used.

12. Teaching Pedagogies

13. Flipped Classroom
 This model inverts or 'flips' the usual classroom paradigm, things are done
the other way round: the teacher “delivers” lectures before class in the form
of pre-recorded videos, and spends class time engaging students in
learning activities that involve collaboration and interaction

14.  AIM: Results and observations of implementing a flipped classroom to teach an
introductory programming course (CS1) and how it compares to a traditional
lecture-style approach
 SUBJECT: 3 sections of Engineering, engineering technology, and software
engineering undergraduates studying introductory programming using Python
at Arizona State University
 EXPERIMENTAL STRATEGY
 2 experimental sections in which one half of the course was taught using flipped
approach and second half using traditional approach; 1 control section taught
using traditional approach
 All in-class assignments were game-based and the game-based videos
necessary for solving the in-class assignments were specifically recorded to
achieve student success
 A total of 22 videos were recorded for teaching, 10 assignments given to each
student
 Mid term and final assessment exams were taken as well as pre and post
student surveys to compute self-efficacy
Amresh, A., Carberry, A. R., & Femiani, J. (2013, October). Evaluating the effectiveness of flipped
classrooms for teaching CS1. In Frontiers in Education Conference, 2013 IEEE (pp. 733-735).

15.  FINDINGS:
 Summative assessments suggest that the flipped model produced higher
average scores compared to traditional model in all sections
 Computing self-efficacy from flipped classes revealed an increase from pre
(M = 53.3) and postscores (M = 71.8). A paired-samples t-test of the 39
students confirmed this difference to be significant [t (38) = -3.459, p ≤
0.001]
 A correlation analysis between computing self-efficacy and students'
perceptions of value toward the flipped classroom model was shown to be
not significant.
 Critical student feedback: Adapting to a flipped classroom approach is
overwhelming; viewing long static videos can be boring; a time-constrained
setting to complete assignments can be intimidating in the early stages of
using this approach.
AVERAGE ASSIGNMENT, MIDTERM, AND FINAL SCORES

16. Peer Instruction
 Peer instruction is about students teaching each other (their peers),
where first a multiple choice question (concept test) is posed by the
lecturer in class, students vote on an answer using clickers, they
then discuss the question and answers with their neighbours in the
lecture, then they vote again on the same question, and finally there
is a class-wide discussion of the question
 This process is often accompanied by quizzes of prior reading and
mini-lectures during class.
 PI provides student-centered learning environment by replacing
some of lecture time’s traditional “sage on the stage” activity with
“guide on the side” student-focused activity.

17.  AIM: Describe results of applying PI model in introductory Java-based CS1
and CS1.5 courses with complete process description, types of questions
asked of students with report on students performance and their opinions
 SUBJECT: 94 Students of introductory CS1 in Winter 2009 and 69 of CS1.5
in Spring 2009 at University of California
 EXPERIMENTAL PROCEDURE
 Textbook reading was assigned before each class, although no reading
quizzes or mini lectures were used
 PI vote-discuss-vote format on clicker questions was used
 Results of first vote were always hidden before discussion and correct final
answer was indicated after discussion of reasonable explanation for right
as well as wrong answers
 Students were also repeatedly presented with benefits of PI model for
learning
Simon, B., Kohanfars, M., Lee, J., Tamayo, K., & Cutts, Q. (2010, March). Experience report: peer
instruction in introductory computing. In Proceedings of the 41st ACM technical symposium on
Computer science education (pp. 341-345). ACM.

18.  Types of questions asked
 Concepts for which common usage errors occur
 Emphasis on concept application
 Eg. Code tracing, selecting the right line(s) of code, explaining in English
words what a code fragment does or describing conditions when a
particular code structure or feature should be used

19. Peer Instruction Questions In Each Class
PI Question Counts by Initial Vote Correctness
 FINDINGS:
 Students’ initial correctness in answering ranged from 15%-86% with an
average of 44-47%.
 Average correctness after discussion was 63-68% with a normalized gain of
35-41%.
CS1 Correctness Before and After Discussion

20. Would you recommend that other instructors in computing
courses use clickers with discussion?
Clickers with discussion is valuable for my learning.
•9-17% of students rarely discussed and 30-33% only sometimes discussed
during group discussion, whilst the remainder always did so.
•Only a minority of the class (20-38%) read textbook most or all of the time. Of
the people who didn’t always read before class, about half of them felt this had
had a negative impact on their ability to learn in class.
Reference website: http://www.peerinstruction4cs.org/

21. Pair Programming
 In pair programming, two students share a laptop, and one of them is the
“driver” who types in the code. The partner – known as the “navigator” –
does not handle the keyboard, but gives verbal feedback as they work on
the problem together.
 Advantages include: code quality improvement, increased number of
students passing the course, increased student enjoyment, lower levels of
frustration and reduced instances of cheating, develop communication skills
and team work
 Concerns : Active participation by all students is required, Freeloading
behind team members

22.  AIM: Assess students using peer evaluation and random pair assignment in
collaborative programming assignments in CS1
 EXPERIMENTAL PROCEDURE
 Random selection of teams to pair 2 students together for each assignment
with one of them being assigned as a team lead
 Face to face meetings not compulsory for collaboration
 Student survey asking two questions designed to evaluate their teammate
after each assignment
Survey questions asked
after every
programming
assignment
Urness, T. (2009). Assessment using peer evaluations, random pair assignment, and collaborative
programing in CS1. Journal of Computing Sciences in Colleges, 25(1), 87-93.

23.  FINDINGS
 Average assignment quality over the course of seven programming
assignments greatly increased during pair programming
 The exam scores did decline slightly when pair programming was used
although comparable to the previous session (90% vs. 87.7%)
 Working in a team provides motivation by making a student accountable to
another student in the class
 Survey questions prompt the students to contact each other shortly after
the assignment is posted.
 Collaborating on code allows someone else to see possible mistakes or
overlooked points.
 Fewer students were found frustrated during office hours and very few
instances of pair incompatibility were seen

24. Average exam scores of two semesters of CS1
Average assignment scores of two semesters of CS1

25. Visualization based
Programming
 In this strategy, a visual programming language is generally used to teach
the basic computing concepts in introductory CS to the students
 Visual programming environments provide graphical or iconic elements
which can be manipulated by users in an interactive way according to some
specific spatial grammar for program construction
 Benefits of this approach include sustained student interest and enjoyment
in the course, low dropout rates and motivation to learn computing
 Most common programming languages used in this approach include
Scratch and Alice

26. Greenberg, I., Kumar, D., & Xu, D. (2012, February). Creative coding and visual portfolios for CS1.
In Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 247-
 AIM: design and development of a new approach to teaching the college-level
introductory computing course (CS1) using the context of art and creative
coding and its comparison with other approaches
 SUBJECTS: 23 students of Bryn Mawr College and 16 of Southern Methodist
University (SMU) were taught CS1 in Fall 2010 using Processing programming
language
 EXPERIMENTAL PROCEDURE
 Major topics covered: creative computing, drawing primitives, interactivity,
simulation, control structures, arrays, functions, objects, text, data and
visualization
 Students were asked to create a visual portfolio of their aesthetic creative
coding assignments that employ basic computing structures using Processing
 A larger collaborative project (virtual fish tank) between the students of the two
partner institutions Bryn Mawr College and SMU was given mid-semester for
team learning
 A final design project was also given where students chose, designed, and built
a data visualization artifact of their own interest

27.  FINDINGS
 21 Bryn Mawr Processing CS1 students, 11 SMU Processing CS1 students and 39
SMU non-Processing Java-based CS1 students returned the surveys along with 22
and 24 surveys from Spring 2007 and Spring 2008 classes respectively of CS1 with
robots taught at Bryn Mawr
 Students in the Processing sections appear more positively inclined to take
additional CS courses
 Students in the Processing sections are more likely to spend extra time on a
homework assignment for "fun“
 Students in the Processing sections indicate strong tendency to talk to friends not in
the class about the class
 Students in the Processing sections at both institutions disagree that CS and
programming are the same thing
 SMU students exhibit stronger confidence in knowledge and technical knowhow
(compared to peer in class) than Bryn Mawr students
 SMU students also exhibit stronger confidence in math and science abilities, which is
partly explained by the higher number of intended CS majors in the class.
 Students at both institutions are quite positive about technology and trying new
tools/products, with the SMU students indicating stronger tendencies.

28. % of students responding Agree or Strongly
Agree
% of students responding Yes
% of students responding Agree or Strongly
Agree
% of students responding Yes

29. Problem Posing
 Problem-posing education solves the student-teacher contradiction by
recognizing that knowledge is not deposited from one (the teacher) to
another (the student) but is instead formulated through dialogue between
the two
 Problem-posing contextualizes knowledge and is based on instructor and
learner posed questions as catalysts for learning
 Problem posing involves the asking of new questions around a given
situation by a learner
 The approach is useful in building computational, thinking skills and
confidence among the students

30.  AIM: Investigate how the PPE instructional strategy affects students’
learning and engagement in CS1 course and in what pattern does its affect
varies for advanced learners and the novices
 SUBJECT: 450 students of CS1 course (excluding CS majors) conducted in
Spring 2013 for teaching programming concepts using Scratch and C++
 Experimental Strategy:
 Students were asked in pairs to generate two challenging problems & their
solutions for topics learnt uptil 4 week lab classes for five days continuously
 Student assessment tests taken for pre (30 marks quiz) and post (50 marks
exam) PPE week
 Anonymous student surveys were taken for measuring learning perception
and engagement
 Student Questions were evaluated based on difficulty, computational
thinking and creativity levels
Mishra, S., & Iyer, S. (2013, December). Problem Posing Exercises (PPE): An instructional strategy for learning of
complex material in introductory programming courses. In Technology for Education (T4E), 2013 IEEE Fifth
International Conference on (pp. 151-158). IEEE.

31.  Findings of student surveys and test scores
Quality
(Difficulty) of
Generated problem
Level 1
(Low), N=32
Level 2
(Medium),
N=83
Level 3
(High), N=20
Mean of [PostPre] Scores (out of
100)
1.04 7.59 4.83
Table showing difference of scores [posttest – pretest] for different groups of students, generating low
level, medium level, and high level of questions

32. 42% of students agreed to the positive effect of PPE on their learning
50% of students felt that PPE made CS1 interesting
Majority of students, irrespective of being advanced or novice learner, generated
problems of medium level difficulty and PPE was found to be more effective for
novice learners than advanced learners

33. Three – Layer Strata Transition
Diagram for Advanced Learners
(No. of Samples=62)
Three – Layer Strata
Transition Diagram for
Novice Learners (No. of
Samples=60)

34. THANK YOU!
QUESTIONS?

35. REFERENCES
 Mason, R., Cooper, G., & de Raadt, M. (2012, January). Trends in introductory programming courses in
Australian universities: languages, environments and pedagogy. In Proceedings of the Fourteenth Australasian
Computing Education Conference-Volume 123 (pp. 33-42). Australian Computer Society, Inc.
 Davies, S., Polack-Wahl, J. A., & Anewalt, K. (2011, March). A snapshot of current practices in teaching the
introductory programming sequence. InProceedings of the 42nd ACM technical symposium on Computer science
education (pp. 625-630). ACM
 Siegfried, R. M., Greco, D., Miceli, N., & Siegfried, J. (2012). Whatever Happened to Richard Reid’s List of First
Programming Languages?. Information Systems Education Journal, 10(4), 24.
 Settle, A. (2012, October). Turning the tables: learning from students about teaching CS1. In Proceedings of the
13th annual conference on Information technology education (pp. 133-138). ACM.
 Amresh, A., Carberry, A. R., & Femiani, J. (2013, October). Evaluating the effectiveness of flipped classrooms for
teaching CS1. In Frontiers in Education Conference, 2013 IEEE (pp. 733-735). IEEE.
 Mok, H. N. (2014). Teaching tip: The flipped classroom. Journal of Information Systems Education, 25(1), 7.
 Simon, B., Kohanfars, M., Lee, J., Tamayo, K., & Cutts, Q. (2010, March). Experience report: peer instruction in
introductory computing. In Proceedings of the 41st ACM technical symposium on Computer science
education (pp. 341-345). ACM.
 Urness, T. (2009). Assessment using peer evaluations, random pair assignment, and collaborative programing in
CS1. Journal of Computing Sciences in Colleges, 25(1), 87-93.
 Khan, S., Ray, L., Smith, A., & Kongmunvattana, A. (2010, December). A Pair Programming Trial in the CS1 Lab.
In Proc. Annual International Conference on Computer Science Education: Innovation and Technology
(CSEIT) (pp. 6-7).
 Greenberg, I., Kumar, D., & Xu, D. (2012, February). Creative coding and visual portfolios for CS1.
In Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 247-252). ACM.
 Mishra, S., & Iyer, S. (2013, December). Problem Posing Exercises (PPE): An instructional strategy for learning of