Li, Fudong

Savage, Nick

Portsmouth University Research Portal (Pure)

   
Demonstrating data carving concepts using jigsaw puzzles: a 
preliminary study 
 
Fudong Li; Nick Savage 
School of Computing, University of Portsmouth, Portsmouth, UK 
Fudong.Li@port.ac.uk;  
Nick.Savage@port.ac.uk  
 
Abstract: According to the non-continuation rates for the 2015-2016 intake published by the Higher Education 
Statistics Agency, almost 11 % of computer science students withdrew from universities after their first year, 
being the highest amongst all subject areas. The reasons for this are varied; including students’ age, health 
issues, the amount of study load, and financial difficulties. However, a lack of motivation has been cited as 
being a significant factor. Within the School of Computing at University of Portsmouth, a number of methods 
are being investigated to enhance the student’s learning and teaching experience in order to decrease 
withdrawal rates. For our BSc (Hons) Cyber Security and Forensic Computing course, students need to master 
various topics. One of these has been conceptually difficult to comprehend due to the high level of abstract 
understanding required; data carving. Within the digital forensic domain, the purpose of data carving is to 
reassemble files from fragments in the absence of file system metadata; those carved files could contain 
valuable artefacts that can be used to prove/disprove alleged offences within a forensic investigation. 
Although the idea of data carving seems to be simple, it does require students to have a deep understanding 
of how data is stored on a storage device and various file identifiers. Based upon the authors’ experience, 
these are difficult for students to grasp without an adequate visualisation. In order to demonstrate the data 
carving concept more clearly and improve the student engagement at the same time, a jigsaw puzzle game is 
used to demonstrate data carving concepts (i.e. reassembling pieces of an object together). During the 2017-
2018 academic year, two groups of Cyber Security and Forensic Computing students were recruited to pilot 
the proposed idea. In total 32 students provided their feedback via a questionnaire after the jigsaw activity. 
84% of the students thought that the puzzle activity helped them to understand the data carving concept; also 
more than four-fifths of the students claimed that they enjoyed the puzzle game. 
  
Key words: computing students, withdrawal rate, student engagement, game based learning, data carving, 
jigsaw puzzle. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1. Introduction 
Within the UK higher education sector, the number of first year student enrolments has grown steadily over 
the period from 2012/13 to 2016/17, with 548,415 student entrants for the year 2016/17 alone (Higher 
Education Statistics Agency (HESA), 2018a). Despite their high level of commitment (including paying £9,000 
tuition fees per year), not all first year students have progressed into the second year of their study; more 
worryingly, the proportion of first years dropping out from university has risen continuously over the last few 
years, notably 5.7%, 6.0%, 6.2%, and 6.4% for academic years 2012/13, 2013/14, 2014/15, and 2015/16 
respectively (HESA, 2018b; HESA, undated). For those who dropped out from the higher education after their 
first year study, their degree programs cover all subjects. However, according to the withdrawal rates for the 
2015-2016 intake published by the HESA, almost 11% of computer science students withdrew from universities 
after their first year, being the highest amongst all subject areas (HESA, 2018b). With the aim to investigate the 
reason why students may withdraw from their studies, several research projects were conducted; their results 
suggest that the reasons for this are varied, such as students’ age, health issues, the amount of study load, and 
financial difficulties (Altin and Rantsus, 2015; Xenosa et al., 2002). However, a lack of motivation has been 
cited as being a signification factor (Kinnunen and Malmi, 2006; Paura and Arhipova, 2014).  
 
At the School of Computing in University of Portsmouth, a number of methods are being carried out to 
enhance the student’s learning and teaching experience in order to decrease withdrawal rates, such as 
providing personal tutoring support and adopting various technologies for teaching. For our BSc (Hons) Cyber 
Security and Forensic Computing course, students need to master various topics, including digital forensic 
investigation principles, computer architecture, operating systems and data carving. Within the digital forensic 
domain, the purpose of data carving is to reassemble files from fragments in the absence of file system 
metadata; those carved files could contain valuable artefacts that can be used to prove/disprove alleged 
offences within a forensic investigation. Although the idea of data carving seems to be straightforward, it does 
require students to have a deep understanding of how data is stored on a storage device and various file 
identifiers; these could be difficult for students to grasp without an adequate visualisation. To this end, the 
paper demonstrates a preliminary study that uses a jigsaw puzzles activity to demonstrate data carving 
concepts and enhance student engagement and learning.  
 
The remainder of paper is structured as follows: Section 2 reviews existing studies that are proposed and used 
for enhancing student engagement and learning. Section 3 describes the proposed method. Section 4 
demonstrates students’ feedback upon the proposed method, along with a detailed discussion. Section 5 
concludes the paper and highlights future research directions.  
 
2. Literature Review  
Due to its importance to teaching and learning (e.g. students learn more when they are engaged), student 
engagement is a well-established domain for educational research (Gettinger and Ball, 2007). Many aspects of 
student engagement have been studied, including types of engagement and strategies that can be used for 
enhancing student engagement. 
 
Based upon prior studies, Fredricks et al. (2004) offer a comprehensive review that summarises the three 
facets of engagement, naming behavioural engagement, emotional engagement and cognitive engagement, 
along with what they are, their various forms, pros and cons in great detail. Also, Fredricks et al. (2004) and 
Fredricks and McColskey (2012) discuss a wide range of techniques that were developed for measuring these 
three facets. Whilst the justification on why positive student engagement is required is being continuously 
researched, various strategies are also being designed, developed and tested. Amongst those strategies, game-
based learning is about the use of games to enhance students’ learning experience (Plass et al., 2015). 
Jovanovic and Chiong (2012) suggest that games can help learners to improve various important skills, 
including problem-solving, communication and non-linear thinking patterns. 
 
Within the computer science domain, a number studies were conducted focusing upon the use of games to 
help students to learn programming, such as Muratet et al. (2009), Kazimoglu et al. (2012) and Schafer et al. 
(2013). In additional, students can learn programming via a range of games, including CodinGame, Screeps and 
Vim Adventures (Mybridge, undated). To date, little research has been conducted on how to utilise game 
 
 
 
based learning to help cyber security and forensic computing students to comprehend various related 
subjects. As a result, this paper proposes the idea of utilising a well-known game to demonstrate the data 
carving concept and enhance student learning. 
 
3. Methodology  
Once the idea of using a game-based learning method for teaching digital forensic subjects is formed, an 
activity that utilises jigsaw puzzles is designed and implemented to facilitate the data carving teaching session 
in three phases. During the preparation phase, 12 individual jigsaw puzzle sets are selected with each 
containing different number of pieces (ranging from 9 to 36). Then, a number of pieces are purposely removed 
from several random selected jigsaw puzzle sets; this is to simulate various data carving scenarios, including 
files that can be fully carved and partially carved (as demonstrated in Figure 1). Finally, the remaining pieces 
from all 12 sets are mixed together as if they were file segments that are stored on a data storage device. At 
the implementation stage, grouped students are tasked to carry out two activities: 1) retrieve all pieces of one 
puzzle from the collection; this can be achieved based upon the colour coding of the backside of each puzzle; 
and 2) reassemble all available pieces to complete the puzzle. After the puzzle activity, students are asked to 
provide their feedback by completing a survey which only contains two 5-point Likert Scale questions and one 
open ended question. The first Likert Scale questions is used to explore whether the jigsaw puzzle activity 
could help the student to understand the data carving concept better; the second is used to check whether the 
student enjoyed the activity. The open ended question is used to obtain any comments that the student may 
have regarding the activity.  
 
    
        a           b            c                 d 
Figure 1: Examples of data carving scenarios (a: full carved; b, c and d: partially carved) 
This activity was introduced to students during the 2017/18 academic year. In total 45 students participated 
the activity, while 32 of them completed the questionnaire either via a paper based survey or through an 
online based quiz, both of which had the exactly same set of questions. Details of the students’ feedback on 
the proposed activity are presented in the next section.  
 
4. Results and Discussions 
As illustrated in Figure 2, 45% of the participants (out of 32) strongly agreed that the puzzle activity helped 
them to understand the data carving concept; while 39% somewhat agreed. In comparison, only two of the 
students thought they did not benefit from the activity; and none of the students were strongly opposed the 
idea.         
 
 
 
 
 
Figure 2: Participants’ answers on the usefulness of the puzzle activity on learning the data carving concept 
 
When asked whether they enjoyed the activity, 42% of the participants strongly indicated that they did enjoy 
the activity; also the same proportion (i.e. 42%) of participants found the activity somewhat enjoyable. In 
contrast, only 3% of the students (i.e. 1 in 32) claimed that they did not find the activity somewhat enjoyable. 
None of the participants reported that they did not completely enjoy the activity.   
 
 
Figure 3: Participants’ responses on whether they enjoyed the activity 
 
Regarding the response to the open ended question, similar patterns are found as those being observed from 
the two Likert Scale questions. Students found the proposed activity helped them to learn the topic as one 
claimed that “It was good as it made me more aware of the parts that could be missing from a file and that 
data carving is basically piecing together files bit by bit”; also another commented that this was a “Good and 
simple exercise that fully explains the data carving concept”. Students also confirmed that the proposed 
activity was enjoyable, as one stated that “it was fun :D”; and more importantly, students remarked that the 
proposed activity is “Enjoyable; different ways of engaging are always welcome”.  
 
As demonstrated by the results, the proposed method did assist the students in comprehending the data 
carving concept that is an abstract digital forensic subject via the visualisation aid of the jigsaw puzzle. Also, 
the activity is relatively easy to set up. Students enjoyed the proposed learning activity; this is also confirmed 
by the authors’ observation as students showed better engagement and excitement during and after the 
activity. As a result, it is envisaged that the students will improve their learning as they are more engaged 
during the teaching session (Coates, 2005; Graham et al., 2007). To extend from this argument, it is highly 
likely that engaged students will progress further in their higher education life and hence the number of 
withdrawal students will be reduced (Kuh et al., 2008). Due to the initial success of the proposed method, it is 
envisaged that the jigsaw puzzle game can be used in teaching and learning for other computer science related 
subjects, such as searching (e.g. regular expression) and file systems (e.g. master file table for New Technology 
File System). 
 
 
 
 
Nonetheless, the proposed method would be more effective if the following were considered. From the 
implementation point of view, the complexity of the selected jigsaw puzzle needs to be increased and it should 
be adequate for adult learners. Otherwise students may find that the proposed method is too simple (i.e. not 
intellectual challenging) and disengage from the learning (Murray et al., 2004). Also, multiple sets of the same 
puzzle should be utilised to ensure that students will have equal learning experience as they can solve the 
same set of problems rather than each faces a subset of the problems individually (e.g. only files with header 
being missing). From the evaluation standing point, a comprehensive questionnaire should be developed, 
allowing other aspects of the proposed method, such as its effectiveness in students’ learning on the chosen 
topic, to be assessed. Also, a more comprehensive questionnaire will enable sophisticated statistical analysis 
(e.g. correlation) being applied to understand the usefulness of the proposed method. 
 
5. Conclusion 
This paper has presented the use of a novel game-based learning method to demonstrate the data carving 
concept via jigsaw puzzles to improve student engagement and hence reduce student withdrawal rate within 
the computer science domain. Also, feedback from the students shows that the proposed method is effective 
for enhancing their learning. In future, an enhanced version of the proposed method will be devised and its 
usefulness will then be investigated.  
Reference  
Altin, H. and Rantsus, R. (2015) “Why Students Fail to Graduate ICT-related Curricula at University Level”, 
Proceedings: 9th International Technology, Education and Development Conference Madrid, 2nd–4th of 
March, 2015. Eds. Abbr L. Gómez Chova, A. López Martínez, I. Candel Torres, pp. 5364−5368  
 
Coates, H. (2005) “The Value of Student Engagement for Higher Education Quality Assurance”, Quality in 
Higher Education. 11 (1), pp. 25–36. 
 
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. (2004) “School engagement: Potential of the concept: State of the 
evidence”, Review of Educational Research, 74, pp. 59-119.   
 
Fredricks, J. and McColskey, W. (2012) “The Measurement of Student Engagement: A Comparative Analysis of 
Various Methods and Student Self-report Instruments”, In: Christenson S., Reschly A., Wylie C. (eds) Handbook 
of Research on Student Engagement. Springer, Boston, MA 
 
Gettinger, M. and Ball, C. (2007) “Best practices in increasing academic engaged time”, Best practices in school 
psychology V (pp. 1043-1075). Bethesda, MD: National association of School Psychologists 
 
Graham, C.R., Tripp, T.R., Seawright, L. and Joeckel, G.L., (2007) “Empowering or Compelling Reluctant 
Participators Using Audience Response Systems”, Active Learning in Higher Education. 8 (3), pp. 233–258. 
 
HESA (2018a) “Higher Education Student Statistics: UK, 2016/17 – Summary”, available from: 
https://www.hesa.ac.uk/news/11-01-2018/sfr247-higher-education-student-statistics, date accessed 05 June 
2018 
 
HESA (2018b) “Non-continuation: UK Performance Indicators 2016/17”, available at: 
https://www.hesa.ac.uk/news/08-03-2018/non-continuation-tables, date accessed: 06 June 2018  
 
HESA (undated) “Summary – UK Performance Indicators 2015/2016”, available at: 
https://www.hesa.ac.uk/data-and-analysis/performance-indicators/summary/2015-16, date accessed: 06 June 
2018 
 
Jovanovic, J. and Chiong, R. (2012) “Introduction to the Special Section on Game-based Learning: Design and 
Applications (GbL)”, Interdisciplinary Journal of Information, Knowledge, and Management, Volume 7, pp. 201 
– 203 
 
 
 
Kazimoglu, C., Kiernan, M., Bacon, L. and MacKinnon, L. (2012) “Learning Programming at the Computational 
Thinking Level via Digital Game-Play”, Procedia Computer Science Volume 9, 2012, pp. 522-531 
 
Kinnunen, P., and Malmi, L. (2006) “Why students drop out cs1 courses?” In Proceedings of ICER 2006, ACM, 
pp. 97–108.  
Kuh, G.D., Cruce, T.M., Shoup, R., Kinzie, J. and Gonyea, R.M. (2008) “Unmasking the Effects of Student 
Engagement on First-Year College Grades and Persistence”, Journal of Higher Education. 79 (5), pp. 540–563 
 
Muratet, M., Torguet, P., Jessel, J. and Viallet, F. (2009) “Towards a Serious Game to Help Students Learn 
Computer Programming”, International Journal of Computer Games Technology, Volume 2009, Article 
ID 470590 
 
Murray, S., Mitchell, J., Gale, T., Edwards, J. and Zyngier, D. (2004) “Student disengagement from primary 
schooling: a review of research and practice”, CASS Foundation, available at: 
http://www.cassfoundation.org/2016/wp-content/uploads/2016/07/StudentDisengagement.pdf, date 
accessed 20 May 2018  
 
Mybridge (undated) “12 Free Games to Learn Programming”, available at: https://medium.mybridge.co/12-
free-resources-learn-to-code-while-playing-games-f7333043de11, date accessed 15 June 2018 
 
Paura, L. and Arhipova, I. (2014) “Cause Analysis of Students’ Dropout Rate in Higher Education Study 
Program”, Procedia – Social and Behavioral Sciences, Volume 109, pp. 1282-1286  
 
Plass, J., Homer, B. and Kinzer, C (2015) “Foundations of Game-Based Learning”, EDUCATIONAL 
PSYCHOLOGIST, 50(4), pp. 258–283 
 
Schäfer, A., Holz, J., Leonhardt, T., Schroeder, U., Brauner, P. and Ziefle, M (2013) “From boring to scoring – a 
collaborative serious game for learning and practicing mathematical logic for computer science 
education”, Computer Science Education, 23:2, pp.87-111 
 
Xenosa, M., Pierrakeasa, C., and Pintelasb, P. (2002) “A survey on student dropout rates and dropout causes 
concerning the students in the Course of Informatics of the Hellenic Open University”, Computers & Education 
39, pp. 361–377 
 
 
 


Demonstrating data carving concepts using jigsaw puzzles: a preliminary study

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Demonstrating data carving concepts using jigsaw puzzles: a preliminary study

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