Production and Evaluation of Educational Material Using Augmented Reality for Teaching the Module of “Representation of the Information on Computers” in Junior High School

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DOI: 10.4236/ce.2016.79134    1,630 Downloads   2,747 Views   Citations

ABSTRACT

The purpose of this study was the investigation of the added value of technology of Augmented Reality in education and, particularly, whether this contributes to both student performance improvement, as well as the appearance of the psychological condition of Flow, which, according to research, has had a positive effect on their performance when experienced during learning process. The research involved a total of 42 students in their second year of junior high school who were taught the module “representation of the information on computers” using two different technologies, those of Augmented Reality and the Web. Research data showed that both technologies contributed to student performance improvement and to the appearance of Flow to pupils, with apparently better results with the student group who utilized the technology of Augmented Reality, though.

Cite this paper

Giasiranis, S. and Sofos, L. (2016) Production and Evaluation of Educational Material Using Augmented Reality for Teaching the Module of “Representation of the Information on Computers” in Junior High School. Creative Education, 7, 1270-1291. doi: 10.4236/ce.2016.79134.

Received 11 May 2016; accepted 19 June 2016; published 22 June 2016

1. Introduction

Although learning is not something new, educational technology is. Only a few decades ago, few people had the privilege to have the availability of technology that could help them learn. Nowadays, technology in general and educational technology in particular has been rapidly evolving as well as being utilized in both formal and informal education. Computers, mobile phones, interactive whiteboards, videos, multimedia applications, educational games and learning platforms, simulations, virtual reality, Internet and Web 2.0 applications are just some technology examples, which have been effectively used by teachers and students in educational environments (Dror, 2008) .

Nowadays, the new technology of Augmented Reality has emerged in the field of education and up-to-date research shows that its use can have very positive learning outcomes. Such examples constitute research projects by Kerawalla, Luckin, Seljeflot and Woolard (2006) , who searched the potential of Augmented Reality in teaching the Earth-Sun interaction and day-night consecution, the research programme Learning Physics through Play (Enyedy, Danish, Delacruz, & Kumar, 2012) concerning a series of scientific research on the teaching of Newtonian force and motion, the EcoMobile programme (Kamarainen et al., 2013) concerning the use of the particular technology in environmental education and a large number of research games in open spaces, such as Outbreak at MIT, Environmental Detectives, Gray Anatomy etc. (Dunleavy & Dede, 2014) .

In Greece, Augmented Reality has been slightly used in education. The majority of applications concerned its use in open spaces of archaeological interest or inner museum and technology park spaces (Gialouri, 2011; Grigoraki, Politi, & Tsolakos, 2013; Siampanopoulou 2014; Sintoris, 2014) . However, cases where Augmented Reality is used in the classroom, such as the case of Dimitriou (2009) who created an Augmented Reality application for the teaching of electrical circuits to high school students, almost do not exist.

Thus, the research on the use of Augmented Reality in a classroom and the total absence of its applications for the subject of Information Technology is relatively small scale, at least in Greek reality. The present research was carried out in order to fill in both gaps, contributing to the further investigation of its pedagogical value. The answers to be given upon its completion, can highlight a different aspect of the use of Augmented Reality in the educational process, encourage more researchers to explore its educational value, not only for the subject of IT in junior high school but also for other subjects and educational levels and, finally, inform teaching practitioners about the new technology and motivate them to start using it more often during their teaching sessions.

2. Review of Relevant Research Projects

Through an expanded bibliographical review, 31 relevant research projects were identified. All of them had Augmented Reality as their application field, posed pedagogical aims and were held within or/and outside the classroom, with the participation of pupils or students. The following paragraphs summarize the most important results of these research projects.

Students, coming in contact with the technology of Augmented Reality for the first time, are impressed by the way virtual elements are incorporated into the environment they are located, and, as a result, they are motivated and actively participate in course activities (Klopfer et al., 2005; Seo, Kim, & Kim, 2006; Freitas & Campos, 2008; Dunleavy, Dede, & Mitchell, 2009; Liu & Chu, 2010; Wijers, Jonker, & Drijvers, 2010; Cai, Wang, Gao, & Yu, 2012; Dünser, Walker, Horner, & Bentall, 2012; Salvador-Herranz et al., 2013; Cai, Chiang, & Wang, 2013; Chen, Liu, & Lu, 2013; Di Serio, Ibáñez, & Kloos, 2013; Fleck & Simon, 2013; Kamarainen et al., 2013; Wojciechowski & Cellary, 2013; Cai, Wang, & Chiang, 2014; Ibáñez, Di Serio, Villarán, & Kloos, 2014; Ahn & Choi, 2015; Tarng, Ou, Yu, Liou, & Liou, 2015) .

During teaching sessions, they express their enthusiasm for what they do (Klopfer et al., 2005; Kerawalla et al., 2006; Freitas & Campos, 2008; Liarokapis & Anderson, 2010; Wijers et al., 2010; Cai et al., 2014) , collaborate on a great degree with one another in order to achieve their objective ( Klopfer et al., 2005 ; Dunleavy et al., 2009; Liu & Chu, 2010; Fleck & Simon, 2013; Kamarainen et al., 2013; Lin, Duh, Li, Wang, & Tsai, 2013; Ahn & Choi, 2015 ) and, in a lot of cases, are absorbed in what they do in such a degree that they sense a modification of time or decreased reflex (Dunleavy et al., 2009; Liu & Chu, 2010; Cai et al., 2012; Salvador-Herranz et al., 2013; Fleck & Simon, 2013; Ibáñez et al., 2014) .

At the end of the teaching session, they have a positive attitude towards the technology used and claim to be eager to use it again (Núñez, Quirós, Núñez, Carda, & Camahort, 2008; Juan, Toffetti, Abad, & Cano, 2010; Cai et al., 2012; Salvador-Herranz et al., 2013; Cai et al., 2013; Wojciechowski & Cellary, 2013; Cai et al., 2014; Tarng et al., 2015) . They consider it easy to handle (Shelton & Hedley, 2002; Sin & Zaman, 2010; Liarokapis & Anderson, 2010; Liu & Chu, 2010; Wijers et al., 2010; Salvador-Herranz et al., 2013; Wojciechowski & Cellary, 2013; Tarng et al., 2015) , effective because it helped them learn (Liu & Chu, 2010; Wojciechowski & Cellary, 2013; Tarng et al., 2015) and apt to help them learn more (Sin & Zaman, 2010; Liu & Chu, 2010; Salvador-Herranz et al., 2013; Wojciechowski & Cellary, 2013) , although do not hide their satisfaction for what they have achieved by using it (Liu & Chu, 2010; Salvador-Herranz et al., 2013; Di Serio et al., 2013; Wojciechowski & Cellary, 2013) .

The accuracy of the students’ views seems to reflect on their learning outcomes. After the use of technology, they have better performance than before (Shelton & Hedley, 2002; Seo et al., 2006; Nischelwitzer, Lenz, Searle, & Holzinger, 2007; Juan et al., 2010; Sin & Zaman, 2010; Liu & Chu, 2010; Wijers et al., 2010; Pasaréti et al., 2011; Cai et al., 2012; Dünser et al., 2012; Salvador-Herranz et al., 2013; Chen et al., 2013; Fleck & Simon, 2013; Kamarainen et al., 2013; Lin et al., 2013; Cai et al., 2014; Ibáñez et al., 2014; Ahn & Choi, 2015; Tarng et al., 2015) , however, not when they do not handle the application themselves (Cheng & Tsai, 2014) , they improve the spatial perception (Shelton & Hedley, 2002; Núñez et al., 2008) they are able to observe objects, which, under normal circumstances, they are not able to, either because of their size (too big or too small) or because they are not visible in the environment (Dunser et al., 2012; Fleck & Simon, 2013; Kamarainen et al., 2013; Ibáñez et al., 2014 ), they retain their knowledge for longer periods (Cai et al., 2012; Cai et al., 2013) and it seems that students of low or medium initial performance benefit more, on the basis of their knowledge test results before the use of Augmented Reality, whereas students with very good initial performance did not show expected improvement (Shelton & Hedley, 2002; Freitas & Campos, 2008; Cai et al., 2013; Cai et al., 2014) .

3. Theoretical Framework

The term Augmented Reality refers to such technology which increases the sense of reality, allowing the coexistence of digital and factual information in the same environment (Azuma, 1997) . Unlike Virtual Reality which completely substitutes real world, the user is capable of not only simply seeing digital elements but also communicating and exchanging data, interacting with them.

Nowadays, teachers have been offered two different types of Augmented Reality applications. Those based on the user’s location (location-based) and exclusively use portable devices to project augmented information on screen and the ones based on the existence of an object or an image (image-based) and are able to use either a portable device (Dunleavy & Dede, 2014) or a personal computer (PC) with a camera (Cheng & Tsai, 2013) , or even a Head Mounted device (HMD) (Yuen, Yaoyuneyong, & Johnson, 2011) . The first type of applications is suitable for exploratory activities outside the classroom, such as games, visits to archaeological sites and museums, while the second, is suitable for skills-building and knowledge acquisition activities inside the classroom (Cheng & Tsai, 2013) .

Research in web environments (Webster, Trevino, & Ryan, 1993; Liao, 2006; Shin, 2006) , in games and in virtual reality environments (Papastergiou, 2009; Faiola, Newlon, Pfaff, & Smyslova, 2013) have showed that students’ learning outcomes can be enhanced if students experience the psychological condition of Flow during teaching and several researchers have already recognized that this positively supports their learning (Pearce, Ainley & Howard, 2005; Kye & Kim, 2008; Choi & Baek, 2011) . Augmented Reality as a means which shares common features with virtual reality, is expected to help students develop Flow.

The state of “Flow” can be described as the psychological situation of someone who is involved in a pleasant and enjoyable, for himself, activity in the course of which they appear to be totally preoccupied in what they do. In order to be found in such a psychological situation, they have to meet two factors which play the most important role: (1) the, perceived by them, difficulty of challenge they have to face and (2) their, perceived by them, skill to deal with this challenge. Therefore, even a low difficulty activity is able to induce Flow state when there is balance between these two factors. In the case of imbalance, a person can feel Anxiety when they consider that they have a lower degree of skills than those needed to complete the activity and Boredom when the opposite happens. The relation between these two factors has been represented on a model (Figure 1), where the psychological state of Flow constitutes a channel (Csikszentmihalyi, 1975) .

Generally speaking, nine factors relate to the appearance of “Flow” (Jackson & Csikszentmihalyi, 1999) , without excluding the existence of others (Finneran & Zhang, 2005) : (1) challenge-skill balance, when both are at a high level and in balance with one another, (2) action-awareness merging, when everything occurs spontaneously and automatically, (3) clear goals, when the person knows what to do, (4) unambiguous feedback, when the person immediately knows whether they have achieved their goals, (5) concentration on task at hand, when

Figure 1. Initial model of “Flow”.

the person is fully concentrated on and preoccupied with what they do, (6) sense of control, when the person feels they have their actions under control and can cope with anything which may occur (7) loss of self-cons- ciousness, when the person loses their sense of self, (8) transformation of time, when the person feels that time has passed very quickly, or has lasted for centuries and (9) autotelic experience, when the person considers that the effort made was worth it.

A necessary condition to make the use of each and every form of technology effective in an educational framework is its proper teaching use (Sofos, 2011) . What is important is not technology itself, but the way it is used to support learning (Bronack, 2011) .

A teaching session is characterized successful by the degree of achievement of learning outcomes expected by the teacher at the end of each session. The existing objective difficulty in this kind of control is the way in which what the student has learned will be reliably tested, since the biggest part of his thought is not visible to others. To overcome this difficulty, the teaching practitioner resorts to search for clues that will certainly indicate knowledge acquisition. These clues become visible through an expected behaviour determined during lesson planning and described with the learning objectives and performance objectives. The learning objectives are more generally set in relation to the performance objectives. Therefore, there may be the case where a learning objective may be equivalent to a set of performance objectives. However, both describe an action or behaviour which can be observed and thus be controlled (Rellos, 2006; Oosterhof, 2010) .

What must be ensured during objectives description is that a student’s performance constitutes a representative indicator of the skill being tested. What can help at this stage is the knowledge of the skills types as proposed by Bloom (1956) and formed the basis for two out of the three categories used by modern cognitive psychologists, that is the declarative and procedural knowledge (the third is problem solution) (Oosterhof, 2010) .

Declarative knowledge corresponds to the first step of Bloom’s objectives taxonomy, Knowledge (Oosterhof, 2010) . The purpose of learning happening here is the storage of information in the student’s memory and its recall and presentation later, almost in their original form. Procedural knowledge, on the other hand, corresponds to the remaining steps of Bloom’s taxonomy, Understanding, Implementation, Analysis, Synthesis and Evaluation. It is the form of knowledge to be acquired by a student in order to be able to complete an activity and often involves motor skills and cognitive strategies. To evaluate procedural knowledge it is useful to subdivide it into discriminations, concepts/notions and rules and follow a different technique for each one of them. Discriminations refer to students’ reaction to stimuli perceived by their senses and their evaluation is done by asking them to identify the stimulus which is different to the rest. Concepts/Notions refer to examples with particular characteristics which the students are again invited to locate. Finally, rules refer to the principles implementation and ask students to apply them to unknown examples (Oosterhof, 2010) .

4. Purpose and Research Questions

The aim of this study was to investigate the contribution of Augmented Reality technology to the improvement of student performance and the emergence of the psychological state of Flow through a teaching intervention to junior high school second-year students. These students would be taught the “Representation of the information inside a computer” module which is suggested in the curriculum using a digital implementation of Augmented Reality. The results would be compared to the results of a second, equivalent, group of students who would be taught the same module using a different kind of technology, in particular the Web technology.

In order to achieve the goal of this research, the following research questions were posed:

1. Did the use of the Web contribute to the improvement of the learning outcomes of the control group, to what extent and in which knowledge categories?

2. Did the use of Augmented Reality contribute to the improvement of learning outcomes of the experimental group, to what extent and in which knowledge categories?

3. What kind of differences appear between the two groups after the teaching intervention, as far as their overall learning level and the individual categories of knowledge are concerned?

4. Did students in each group experience the psychological state of Flow using their digital applications and which group appeared the strongest state?

5. Did the groups show differences in each of the nine factors related to the psychological state of Flow and how big they were?

5. Method

The research was conducted in the Junior High School of Massari, a regional school on the island of Rhodes. The school was chosen for several reasons such as adequate technological equipment, the willingness and enthusiasm expressed by the students to learn using their tablets and the good cooperation with the school administration.

The second-year class had a total of 42 students divided into two parties, initially equivalent to each other as shown by their performance in the positive subjects of the previous school year. The students of the first party (B1) were 20 and there was equivalence in terms of their gender. Their school performance in the positive subjects of the previous school year curriculum (Mathematics, Physics, and Computer Science) was 14.7 on average. The second party (B2) had 22 students, 10 boys and 12 girls. The corresponding average of their in the positive subjects of previous year curriculum was 15.0.

It should be noted here that the previous year marks of the students were used as a criterion of assessment of students’ initial school performance because the research was conducted at the beginning of the school year (October), during which they had not yet received their marks for the second year class.

The first party constituted the control group, while the second, the experimental group. The selection of the B2 party as the experimental group was according to the sole criterion of the number of students who owned tablets and were eager to bring them to school and use them during sessions. The students of both groups were taught “Unit 1-Digital World” of the school book for the subject of I.T. in Junior High School, following a constructive approach and specifically a teaching scenario of Anchored instruction. Anchored instruction is based on the existence of an “anchor” which usually takes the form of a video. The video-anchor sets a problem and gives students the initial information in order to start solving it. The difference in the teaching approach is identified in the digital tool for the collection of extra information used by each group. The control group used the computer lab computers to collect information from the website http://diadiko.weebly.com in order to solve the problem set by the anchor, while the experimental group used tablets to collect information from an application of Augmented Reality. Both the website and the application of Augmented Reality were created for the research purposes with Weebly and Layar (basic version) tools, respectively, and their contents did not differ.

The first three research questions referred to the investigation of the pedagogical value of the technology of Augmented Reality compared to Web technology and their research data was collected through a quiz given to students beforehand and one week after the teaching intervention. The quiz was developed by the researcher for research purposes and numbered a total of 21 questions, 9 of which related to declarative knowledge and the remaining 12 related to procedural knowledge, of which 4 questions referred to Concepts/Notions and 8 to Rules. Each correct question was given 1 point and every wrong one was given 0.

The last two research questions investigated the occurrence of the psychological state of Flow and the estimation of its intensity degree. The research data was collected using two different questionnaires developed by other researchers. Both were translated and adapted to the knowledge level of the students.

The first one (intermediate Flow questionnaire) was developed by Pearce et al. (2005) and its purpose was to assess more accurately the fluctuation of the Flow, which is more difficult to assess with one and only questionnaire given to students at the end of the research, especially in small-scale surveys such as this. This questionnaire was given to the students in two different teaching phases. It contained two questions of the 5rank Likert scale and investigated the existence of balance between the difficulty of the activity completed by the students using their digital applications and their skills.

The second (final Flow questionnaire) given to students at the end of the research was developed by Jackson & Marsh and had a Cronbach’s reliability indicator a=0.83 (Jackson & Marsh, 1996) . It included a total of 36 questions of the 5rank Likert-type scale (1 = strongly disagree, 2 = disagree, 3 = neither disagree nor agree, 4 = agree, 5 = strongly agree). These questions tried to seek the nine factors which the appearance of Flow is related to and every factor corresponded to four questions which were repeated, differently formulated, every nine questions.

Each question of the final Flow questionnaire was rated from 1 - 5. The total score for each student could range from 36 (total absence of Flow) to 180 (high Flow intensity). Also, the average of each factor could range from 4 (complete absence of Flow) to 20 (high Flow intensity).

In order to answer the research questions of the present study, the research data were analyzed both descriptively using the Microsoft Excel 2010 programme and inductively using the statistical programme SPSS 19.

More, specifically, as far as the inductive analysis is concerned, there was initially a regularity control of the variables through the Shapiro-Wilk test and then, for those variables presenting regularity, depending on the research question, what was chosen was either a parametric t-test of either dependent or independent samples. For the rest of the variables, we selected the corresponding non-parametric test, either the Wilcoxon one or the Mann-Whitney one.

6. Results

6.1. Research Question 1

Initially, there had been regularity control of every variable using the Shapiro-Wilk test, as the sample of the control group (N = 20) was fewer than 50 people. It was found that five variables presented regularity: the variable Procedural knowledge-rules, both before and after teaching intervention, with a significance level of p = 0.054 and 0.070 respectively, the variable Sum of procedural knowledge afterwards with a significance level of p = 0.290 and the variable Total score both before and after teaching intervention, with a significance level of p = 0.193 and 0.142 respectively.

Variable pairs before-after exhibiting regularity, underwent a parametric t-test of dependent samples (paired samples t-test). The results showed a high correlation between the variables Total score before and Total score after (r = 0.654, p < 0.05) and a marginal correlation between the variables Procedural knowledge-rules before and Procedural knowledge-rules after (r = 0.244, p > 0.05) (Table 1). Also, there was a statistically significant difference in the average values of these two variable pairs, at a significance level of p < 0.05 (Procedural knowledge-rules [t(19) = −10.782, p = 0.00], Total Score [t(19) = −10.357, p = 0.00]) (Table 2).

All other pairs of variables (before, after) as well as the variable Sum of procedural knowledge after, whose corresponding variable (Sum of procedural knowledge before) showed no regularity, were analyzed by the non-parametric Wilcoxon test. What became apparent from the results of this analysis was that all three pairs of variables showed a statistically significant difference on significance level p < 0.05 (Declarative knowledge [Z(20) = −3.741, p = 0.00], Procedural knowledge-concepts [Z(20) = −3.926, p = 0.00], Total procedural knowledge [Z(20) = −3.947, p = 0.00]) (Table 3). Moreover, the overall student performance increased by 3.50 points

Table 1. Correlation table of the dependent samples.

Table 2. Control group: Results of the t-test for dependent samples.

Table 3. Control group: Results of the Wilcoxon non-parametric test.

(SD = 1.573) to 11.95 (SD = 4.478) i.e., 8.45 points on average (Table 2).

Finally, the variations in students’ answers were calculated as well as the minimum and maximum number of correct answers in each category aiming at the reflection of the degree of themp.jpg" />

Appendix B: Final Flow Questionnaire

Full Name:_______________________________________ Class: _______

The following questions refer to the activities you did using your PC or tablet. There is no correct of wrong answer. For each question, please choose the number which represents how you felt during the activities.

Appendix C: Quiz

FULL NAME :……………………………………CLASS :……………………………………………………

1. Which of the following signalsdigital?

a.b.c. d.

2. Which is the difference between a digital and an analogue apparatus as far as the form of their data is concerned?

a. in digital apparatuses data is numbers whereas in analogue ones they are texts

b. the rates if their flow data take any rates

c. the rates of their flow data take particular rates

d. they have no difference

3. What kind of apparatus is each one of the following?

4. Refer to at least two advantages of the use of a digital system

1.____________________________________________________________________________________

2.____________________________________________________________________________________

3.____________________________________________________________________________________

5. Choose the correct answer to the question “Which is the computer language?”

6. Which are the “letters” of the computer language?

a. the English alphabet b. each country’s alphabet

c. numbers from 0 to 9 d. numbers 0 and 1

7. What do binary digits (bits) symbolize?

0 symbolizes________________________________________

1 symbolizes ________________________________________

8. Which of the following constitutes a byte?

a. 01101001 b. 0101010 c. 011010 d. 1210000

9. Refer to the byte multiples writing them from the smallest to the biggest

a. ____________

b. ____________

c. ____________

d. ____________

10. Originally, we could key in only English characters. Explain in what way this restriction has been overcome.

_______________________________________________________________________________________

_______________________________________________________________________________________

_______________________________________________________________________________________

11. Nick wrote a paper on his PC. When he opened it on the school’s PC, he discovered that the letters had been jumbled up. When he opened it again on his own PC, the text was normal again. Where seemed to be the problem?

_______________________________________________________________________________________

_______________________________________________________________________________________

_______________________________________________________________________________________

12. What is the name of the common code used by computers to code texts?

a. ΧASKI b. ASCII c. Binary d. ABC

13. How many bytes do we need to code the word “ELLADA” in the computer language?

a. 2 b. 4 c. 6 d. 8

14. Please code the word AEGEAN using the code given below.

15. Please code number 7 in the computer language.

16. Please code the following picture in the computer language.

17. If the picture of the previous exercise (17) had 5 different colours, how many bits each code would consist of?

a. 1 b. 2 c. 3 d. other: __________

18. Decode the text 010010100100011001001011

19. Decode the number 01101101 in the decimal numbering system

_____________

20. Decode the following picture using colours of your choice.

Conflicts of Interest

The authors declare no conflicts of interest.

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