14th European Conference on e-Learning ECEL

14th European Conference on e-Learning ECEL-2015 Hatfield, UK Maths and Mobile Technologies: Student Attitudes and Perceptions Khristin Fabian University of Dundee [email protected] Abstract: Approaches that advocate the contextualized teaching of mathematics have been around for years but the ubiquity of mobile devices together with the potential to bridge classroom learning to real-world has added a new angle to contextualizing mathematics learning. The goal of this research was to examine how the use of mobile technologies affected students’ attitudes towards mathematics as well as student perception about the use of mobile technologies. The study was a month-long mixed methods design and utilized the Micro, Meso and Macro (M3) Level Evaluation Framework. Participants were Primary 6 and 7 students from two Scottish primary schools (N = 48). Students participated in four sessions of mobile-supported, collaborative learning activities that covered topics on geometry and data handling. Students evaluated each session using a semantic differential scale. Student evaluations of the activities were positive (M=3.96, SD=.26). On the sematic differential scale, they rated the activity useful, stimulating and innovative as opposed to irrelevant, distracting and dull. Students were asked to separately rate the activity and the use of the mobile device but no significant difference were found in the ratings. Gender difference in the rating of the activities was present in the first session, with higher ratings from male students on questions relating to user satisfaction, but this did not re-occur in later activities. In the student interviews, students related that the activities were fun, helpful and in some ways, connected the maths topics with their everyday life. There was no significant difference between pre-test and post-test scores in mathematics attitudes but resulted in small effect size in the subscale factors of self-confidence (ES = .20) and mobile use (ES = .26). These results indicate that students have a positive perception on the use of mobile technologies. However, its effect on students’ attitudes towards mathematics needs further investigation. Keywords: mobile learning, tablets, mathematics education, student attitudes 1. Introduction The use of mobile technologies has been gaining wider acceptance in education in recent years with rollouts in private and public educational sectors. In Turkey, for example, the Fatih Project plans to rollout tablet computers in the hands of every student from Grade 5 to Grade 12 (Pouezevara et al., 2013). The appeal to adapt mobile technologies has much to do with its lower costs, increasing ubiquity and its potential benefits in education, making it the technology of choice for one-to-one computing initiatives and bring-your-own-device (BYOD) strategies. Potential benefits of using mobile technologies include: facilitate personalized learning, enable anytime, anywhere learning, support situated learning and enhance seamless learning (Kraut, 2013). Mobile learning is a fairly new field and definitions and focus has varied over the years. Some definitions have focused on the device (Traxler, 2005) while others have focused on the mobility of the learner (Pachler, Bachmair and Cook, 2010). For this study, mobile learning is defined as “learning across multiple contexts, through social and content interactions, using personal electronic devices” (Crompton, 2014: 4). Sawaya and Putnam (2014) proposed an integrated framework to help teachers design mobile learning activities that has the capacity to bridge classroom mathematics to real-world mathematics. The framework consists of three issues to consider when designing learning tasks: (a) learning goals, (b) activity types and lastly (c) affordances of the technology in reference to what mobile devices offer to support mathematics learning. A representation of the framework is shown in Figure 1. These technology affordances are not unique to mobile devices but it is the combination of these affordances in a single device that highlights the potential of mobile technologies in supporting various learning activities.

Maths and Mobile Technologies: Student Attitudes and Perceptions

Figure 1: Framework for the design of mobile learning activities for mathematics (Sawaya and Putnam, 2014) Mobile learning studies on mathematics gained these benefits by connecting learners through mobile phones and social media, allowing students the chance to participate in a one-to-one, student-tutor communication (Roberts & Butcher, 2009); providing anytime or anywhere learning through apps available on iTunes®, Google Play® and the like; as well as using phone sensors for the contextualized learning of mathematics (Shih, Kuo, and Liu, 2012). A review of 32 papers on students’ attitudes and perception on the use of mobile technologies for mathematics found an overall positive response (Fabian, Topping and Barron, 2014). Novelty and learning strategies were some of the factors cited that contributed to the overall student perception. The review also attempted a meta-analysis of students’ attitudes towards mathematics as an effect of using mobile technologies but no conclusive data was drawn. So, while it was apparent that students were enjoying the use of mobile technologies, whether this enjoyment affects their overall attitudes towards mathematics required further investigation. Still, the mobile supported learning activities were able to engage and motivate students by making learning enjoyable and relevant. This paper aims to investigate student perception on the use of mobile technologies for mathematics as well as investigate whether this influence students’ attitudes towards mathematics. Through the more practical and hands-on experiences that can be done with mobile technology, it was expected that students will be more engaged in learning mathematics and thereby facilitate a more positive outlook towards mathematics. 2. Methodology 2.1 Research design and nature of the intervention The study adopted a mixed methods design using the M3 Level Evaluation Framework (Vavoula and Sharples, 2009). M3 provides a “structured format to assess usability, educational and organisational impact and their inter-relationships” (ibid: 12) in three evaluations. The micro level evaluation focused on the user evaluation of the mobile-supported activity. At meso level, evaluation focused on the learning experience. At macro level, evaluation focused on how the use of the mobile device affected students’ attitudes towards mathematics. Students participated in mobile-supported, collaborative learning activities that covered topics on geometry and information handling. The rationale for the design of the activities carried out in this study is derived from the systematic review of literature carried out. In the past, the majority of studies that utilized mobile technologies have used mobile devices as substitutes to computer-based learning activities. Few studies have capitalized on the unique feature of the mobile devices. For example, its mobility feature supports users as they move from one learning context to another while its built in communication channels allows students to collaborate in a networked environment. These features can be harvested to create a maths learning environment that will provide students with hands-on experiences and investigate mathematics concepts in

14th European Conference on e-Learning ECEL-2015 Hatfield, UK their environment. The activities carried out are listed on Table 1 and mapped according to Sawaya and Putnam’s (2015) design framework. Table 1: Activities carried out mapped into Sawaya and Putnam’s (2015) design framework Lesson Task: Students took pictures of symmetrical objects and annotated it with its line of symmetry. Using an application, they also created symmetrical pictures of non-symmetrical objects in their environment. Task: Students investigated area and perimeter of surrounding environment using an application. They also investigated properties of area and perimeter of objects using a manipulative. Students administered surveys on the mobile device. After which they interpreted the data collected and shared the findings with the class.

Affordances Capture Communicate and collaborate Create

Activity Type Practicing math skills Investigating Creating content

Learning Goals Solve problems Form connections Use representations

Compute Communicate and collaborate

Practicing math skills Investigating Applying mathematical problems

Solve problems Form connections

Compute Capture Communicate and collaborate Create

Investigating Applying mathematical problems Creating content

Form connections Use representations

Task: Tasks were encoded in QR codes. Students took pictures of objects that corresponded to certain types of angles. They annotated the pictures to show the angle and its estimated angle measurement.

Capture Communicate and collaborate Create

Practicing math skills Investigating Applying mathematical problems Creating content

Solve problems Form connections Use representations

2.2 Participants Primary 6 and Primary 7 students from two Scottish primary schools (N = 48) were recruited to participate in the tablet-enabled activities. There were 23 male and 25 female students who participated in the study. The schools were selected via self-selecting samples. After the teachers had opted to take part in the research, consent from students and parents from these classes were sought. 2.3 Instruments and measures 2.3.1 Technology used The mobile devices used in the study was budget 7-8 inch tablets of various brands all running Android 4.2 all costing less than £100 each. The rationale for the choice of smaller tablet over the bigger 10-inch screens was because of its portability, as a number of activities are carried out while students move around whilst the 7-8 inch screen size allows two users to conveniently share a screen. 2.3.2 End activity evaluation. The End Activity Evaluation Questionnaire consists of questions derived from Microsoft Desirability Toolkit (Benedek & Miner, 2002) and Lewis’s (1995) After Scenario Questionnaire. The questionnaire was designed to allow the students to rate the activity and the tablet separately. Questions were arranged on a semantic differential scale and grouped in three factors: usefulness, ease of use and user satisfaction.

Maths and Mobile Technologies: Student Attitudes and Perceptions 2.3.3 Maths Attitude Inventory (MAI). The maths attitude inventory used in this study was adopted from two maths inventories: Lim and Chapman's (2013) shorter version of Tapia's (1996) Attitudes Towards Mathematics Inventory and Pierce, Stacy and Barkatsas's (2007) scale to measure students attitudes to mathematics when technology is considered. The resulting inventory is a 20 item test with 5 subscales (1) enjoyment of mathematics, (2) self-confidence, (3) value of mathematics, (4) confidence with technology and (5) learning mathematics with mobile technology. 2.3.4 Group Interviews. Group interviews were designed to draw out student feedback about the activities which might have been missed in the end activity survey. Students recap the activities that they have done so far and were asked to explain which of the activities they liked and least liked. Their opinion as to what the advantages and disadvantages of doing these type of activities were also sought. Students also related the challenges they have experienced in doing these activities. Interviews were audio recorded and transcribed 2.4 Procedure The M3 Evaluation Framework is shown in Table 2 below. Students were given an orientation about the project and about the tablets at the start of the intervention. After which, a pre-test on students’ attitudes towards mathematics was administered. The students participated in mobile-supported, collaborative learning activities that covered topics on geometry and information handling once a week over the course of a month. Each session lasted between 50-60 minutes. These sessions were video recorded using a wearable camera. At the end of each session, students completed an End Activity Evaluation. After four sessions, the maths attitude inventory was again administered followed by a group interview with students. Table 2: M3 Evaluation Framework. M3 Framework Micro-level Meso-level

Instrument End activity questionnaire Student interviews

Macro-level

Maths Attitude Inventory

Measure Student evaluation of the activities Student perception on the use of mobile technology Student attitudes towards mathematics

3. Results 3.1 Micro-evaluation A graph of the semantic differential ratings for the four sessions is shown in Figure 2. All negative items are reverse scored such that all negative items are on the left and positive items are on the right. A higher score means a rating that is in agreement with the positive statement while a lower score means otherwise. For example, in the third item in Session 2 of Figure 2, a mean score of 3.26 means that on average, students found the activity useful more than irrelevant. The average student rating for each item in the evaluation resulted in a mean score of 3.96 (SD=.26) with a range between 3.26 – 4.55. From the graph below, it can be noted that the mean scores for each of the questions are plotted nearer to the right side of the graph which represents the positive adjectives. The usability ratings in Figure 2 were grouped into three subscales of usefulness, ease of use and user satisfaction and further grouped into activity ratings and tablet ratings as shown in Table 3. Each subscale is the average of the rating scores for that category thus giving a range of scores between 0 – 5. The higher the subscale score, the higher the user rating and vice versa. The usability rating of the activities and the tablets were strongly positively correlated on all subscales in all four sessions. This was an expected outcome as students are likely to associate the activity with the mobile device. In the first session, there was a significant difference in user satisfactions with the activity (M = 4.12, SD =.77) and the tablet (M = 4.34, SD = .66); t(36) = -2.456, p = .019. During the third session, there was also a significant difference in the subscales of satisfaction with the activity (M = 4.06, SD = 1.03) and the tablet (M = 4.22, SD =.95); t(42) = -2.038, p = .048) but this significance is rather small.

14th European Conference on e-Learning ECEL-2015 Hatfield, UK

3.26

4.55

Figure 2: End activity ratings for the four sessions; (A) denotes activity rating, (T) denotes technology rating. The ratings were split into tablet ratings and activity ratings. Male students scored higher on the satisfaction subscale for tablets (M = 4.57, SD=.38) than female students (M = 4.06, SD = .82), t(21) = 2.374, p = .027 during the first activity but this difference however did not manifest in the later activities. Table 3: Mean ratings by gender and subscale. Gender Ease of use (Activity) Ease of use (Tablet) Usefulness (Activity) Usefulness (Tablet) Satisfaction (Activity) Satisfaction (Tablet)

Male Female Male Female Male Female Male Female Male Female Male Female

N 22 16 21 17 21 17 22 17 22 17 22 17

Session 1 M (SD) 4.31 (0.71) 3.88 (1.1) 4.27 (0.8) 3.8 (1.21) 4.16 (0.78) 4.17 (0.83) 4.42 (0.66) 4.15 (0.73) 4.19 (0.67) 4.04 (0.9) 4.57 (0.38) 4.05 (0.82)

N 21 23 21 23 21 23 21 23 21 23 21 23

Session 2 M (SD) 3.61 (1.02) 3.68 (1.24) 3.71 (1.04) 3.8 (1.26) 3.94 (0.86) 3.82 (1.17) 3.87 (1.22) 3.75 (1.21) 3.96 (0.81) 3.72 (1.1) 3.93 (0.92) 3.88 (1.23)

N 20 23 20 24 20 24 20 24 19 24 20 24

Session 3 M (SD) 4.24 (0.88) 4.23 (0.93) 4.23 (0.79) 4.28 (0.83) 4.18 (1.17) 4.07 (1.03) 4.2 (1.32) 4.06 (1.07) 4.05 (1.08) 4.06 (1.02) 4.27 (0.92) 4.12 (1.01)

N 19 22 19 22 19 22 19 21 18 20 19 22

Session 4 M (SD) 3.65 (1.78) 3.82 (1.61) 3.79 (1.61) 3.69 (1.55) 3.72 (1.5) 3.64 (1.43) 3.74 (1.56) 3.57 (1.47) 3.5 (1.65) 4.04 (1.13) 3.76 (1.67) 3.74 (1.47)

Meso-Evaluation Ten students from each school (N = 20, 10 male and 20 female) were selected to form the part of the interview based on their pre-test scores on the mathematics attitude inventory and their end activity ratings. The

Maths and Mobile Technologies: Student Attitudes and Perceptions students were a mix of students who scored low, average and high in the two evaluation questionnaires. The interviews were conducted in groups of five where the male and female students were grouped separately with each group interview lasting between 10-15 minutes each. Student satisfaction with the activities The interview findings indicate that students, in general, have a positive outlook on the use of the tablets. These feedbacks, in some ways, validate the students’ activity ratings. Most of the students described the activities as fun (N = 14 out of 20 interviewed) and easy to understand (N = 3) in contrast to what they normally to do. “It’s a variety from what we normally have before, from the technology side of things and the maths side of things actually.” Students (N = 2) who are not secure with their mathematics found the activity fun and challenging. “I find equally challenging but equally like fun. Rather than just sitting down and writing and boring stuff.” However, a couple of students (N = 2), both scored high on the self-confidence subscale but relatively lower in the confidence with technology and learning with mobile technologies subscales of the MAI test commented that they preferred working with books and working with more difficult tasks. “I’m finding it reasonably hard because I’m not a fan of tablets. I find it hard scanning stuff and then finding shapes with a computer. I’d rather just do it myself.” Perceived advantages/disadvantages of doing the tablet-based activities Some students felt that they were engaged in the activities and that they have been more active in their learning (N = 3). While other students (N = 5) felt the activities were helpful in learning mathematics as it is more interactive and allowed them to visualise some of the abstract mathematic concepts. “It’s helping me understand more, like with perimeter I don’t understand it but when we used them, I was like, oh that makes more sense now.” “It’s easier to understand so when the teachers help you in a different way, you probably get it more because you understand it in a different way.“ “I’ve always hated maths but now I quite like it.” In one segment of the interview, one student mentioned that the disadvantage of doing these activities is that he doesn’t get to write on a textbook to which another student responded “the disadvantages for him is the advantages for me.” Apart from that, there were limited responses that lists the disadvantages of the tablets and so discussion usually flowed to the technical challenges encountered. Students felt that these technology issues are the downside of doing these tablet-based activities and sometimes when issues happen, some students were not too motivated to move forward with the activity for the day. This hesitation however is usually set aside by the next activity as students who had issues were again keen to work on the new activity. Challenges encountered The tablets were hooked to a network using a wireless 4G device rather than the school’s network and so, signal would sometimes drop, cutting off a few students from the network. This caused some frustration to the students. One student commented: “A couple of the tablets won’t link. I can’t send it to the teacher. I’m sitting next to him and I can’t send it to them.” Sometimes the applications on the tablet won’t work although it wasn’t to the point of not being able to do things anymore. Most of the time, the breakdowns were just the users not being very familiar with the application.

14th European Conference on e-Learning ECEL-2015 Hatfield, UK Working together Students appreciated the paired work as this allowed them to finish the task (N = 18). However, in one case, a student related that students that understand the app straightaway tend to take over and the other person sometimes does not get a chance to try it out. When asked if they would rather have a one-to-one allocation of devices, all except for two said no. Those that said yes felt that they work better alone, but students who were having difficulty finishing the tasks felt that having just two students to work on the activity is not enough. “If we’re in a pair then you might not know what to do, but if you’re in a group then its better.” “If you’re on a group of 4 and got two tablets, then two of us can go find one thing then another can find another one and then meet back together.” Macro-evaluation The descriptive statistics for the pre-test and post-test scores on the Mathematics Attitudes Inventory (MAI) scale is shown in Table 4. Figure 3 shows the change in student attitudes. From Table 4 and Figure 3, there was a minimal positive change in the scales of enjoyment, self-confidence, value of mathematics and learning math with mobile technology but a negative change in confidence with technology. Paired sample t-tests between pre-test and post-test all showed no significant difference in test scores. However, there was a computed small positive effect size in students’ self-confidence (ES = .26) and learning math with mobile technology (ES = .20). An independent t-test on the differences in pre-test and post-test scores for each MAI scale showed no significant gender difference. Table 4: Pre-test and post-test MAI scores Mean Enjoyment Self-confidence Value of Mathematics Confidence with technology Learning math with mobile technology

Pre-test Post-test Pre-test Post-test Pre-test Post-test Pre-test Post-test Pre-test Post-test

3.18 3.41 3.50 3.82 4.04 4.10 4.14 4.04 3.66 3.87

N

t

SD 41 41 41 41 40 40 41 41 41 41

1.18 1.30 1.25 1.21 0.93 1.01 1.04 1.03 0.98 1.17

Attitude Towards Mathematics

5 4

p-value

Effect size (Cohen’s D) .19

-1.339

.188

-1.930

.061

.26

-.379

.707

.06

.821

.416

-.09

-.970

.338

.20

Enjoyment Self-confidence

3

Value of Mathematics

2

Confidence with technology

1 0 Pre-test

Figure 3: Pre-test and post-test MAI scores

Post-test

Maths and Mobile Technologies: Student Attitudes and Perceptions 4. Discussion 4.1 Limitations of the current study Several limitations regarding the design of the intervention are present in this study. The dependence of the data on self-reports, given that the participants of the study are younger students, is one shortcoming. To mitigate this issue, steps have been taken to ensure that students understand the questions whenever they complete an evaluation. Time and again, students are also reminded about the purpose of the study. However, being a preliminary discussion of an ongoing research, it is acknowledged that the small sample size, the lack of control group and the short duration of the intervention presents issues on the generalisability of the results. These issues are addressed in the bigger study that these partial results are part of. 4.2 Micro, meso and macro evaluations Student evaluation of the activities has been positive. This finding is consistent with most mobile learning research studies. The novelty supported by the technology is largely a factor with the activities. Previous mobile learning studies that look at user acceptance of using mobile technologies tend to not separate user ratings of the activity and the technology (Daher, 2009; Lai et al., 2012). While there was an attempt to separate the ratings between technology and activity, the positive correlation between the two suggests that students might not have objectively evaluated separately. In general, users who had technology issues during the session tended to rate the activity and the tablet on a lower scale. One possible explanation is that in most of these activities, the mobile device is the medium to carry out the learning activity. For example, in session four, when a mobile device had issues scanning a QR code, it was impossible for the students in that pair to carry on with rest of the activity until after some technical assistance. One of the students, at that point refused to finish the activity on a different tablet, while the other student carried on doing the activity on her own. The student who refused to continue with the activity gave a lower rating in both tablet and activity while the student who continued with the task still gave a higher rating for the tablet and the activity and did not account the technical failure earlier experienced. Student ratings are sometimes a reflection of their perceived complexity of the maths topic. For example, where two students felt that they are not very good with angles, despite the angles task (session 4) being similar in format with the symmetry task (session 1), their end activity ratings reflected that. Gender differences favouring male students was present in the initial activities but only for user satisfaction with the tablet use. This did not manifest in further end activity evaluations. While gender differences is a recurring issue in maths and ICT studies, a possible explanation for the lack of difference here is the exposure of participants to tablets and similar devices in their own homes. As with other mobile learning studies (Kong, 2012; Lai et al., 2012), novelty was a contributing factor to student satisfaction. Students contrast the mobile learning activities with what they usually do and although challenging to some students, students’ satisfaction with the activities have remained positive. However, not all students are confident with handling technology and some students work better offline than with technology. This highlights the need for differentiation when offering mobile learning activities. Students felt that they have been engaged more in the activities and enjoyed the aspect of working together. In fact, in more challenging tasks, students prefer that they’d be assigned in bigger groups but still keep the two students per tablet setup. They think that having more students in a group will allow them to work on the activities more efficiently as well as handle the technological issues better. Some students felt that this new way of doing maths has helped them grasp abstract maths concepts and as a result, has helped them improve their attitudes towards mathematics. Although the findings on the MAI scales were not statistically significant, a small effect on students’ self-confidence with mathematics is a promising result given that the intervention has only been for a month. While the use of the tablets has been over-all good, the technical difficulties experienced in some of the activities caused some stress to the students and in some cases deterred students from participating. The issues encountered possibly explains the students lower post-test scores on the Confidence with Technology Scale of the MAI. In the interviews conducted, students explained that while they have used the tablets before and have access to similar devices at home, the nature of use varies with how the tablets were used in the activities. On the whole, however, students were satisfied with the flow of the activities and were keen to continue to participate onto the next phase of the study.

14th European Conference on e-Learning ECEL-2015 Hatfield, UK 5. Conclusion This study investigated student perceptions on the use of mobile technologies. The findings show that students have a positive perception on the use of mobile technologies for learning and these positive perceptions can be attributed to the design of the activities, its ability to engage and motivate students by making the learning tasks enjoyable and relevant. It also highlights the flexibility of mobile devices to support various learning tasks and its capacity to offer students a different way to visualise and contextualise maths concepts. The results on effect of using mobile technologies to students’ attitudes towards mathematics has been limited and needs further investigation. The dependence of this study on self-reporting can be improved by incorporating data that would triangulate results (for example, adding teacher observation to student feedback). This study is a preliminary report of an ongoing research thereby addressing the issues short intervention time and lack of control group. 6. References Benedek, J., and Miner, T. (2002) ‘Measuring desirability: New methods for evaluating desirability in a usability lab setting’, Proceedings of Usability Professionals Association, Orlando, USA, pp 8-12. Crompton, H. (2014) ‘A historical overview of mobile learning: Toward learner-centered education’ in Berge, Z. L. & Muilenburg, L. Y. (eds.) Handbook of mobile learning, Kentucky: Routledge. Daher, W. (2009) ‘Students’ perceptions of learning mathematics with cellular phones and applets’, International Journal of Emerging Technologies in Learning, Vol. 4, no. 1. Fabian, K., Topping, K. and Barron, I. (2014). “Math and Mobile Technologies: A Systematic Review”, Paper presented at European Conference on Technology in the Classroom, Brighton, UK, July. Kraut, R. (2013) UNESCO policy guidelines for mobile learning, France: UNESCO. Kong, S. C. (2012) ‘Using mobile devices for learning in school education’, 2012 IEEE Seventh International Conference on Wireless, Mobile and Ubiquitous Technology in Education, Takamatsu, Japan, pp 172-176. Lai, A.F., Lai, H.Y., Shen, V., Tsai, I., and Chou, A. (2012) ‘The evaluation of two-stage mobile learning guidance of math in an elementary school’, Wireless, Mobile and Ubiquitous Technology in Education, Takamatsu, Japan, pp 282-286. Lewis, J. R. (1995) ‘IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use’, International Journal of Human‐Computer Interaction, Vol. 7, No. 1, pp 57-78. Lim, S. Y., and Chapman, E. (2013) ‘Development of a short form of the attitudes toward mathematics inventory’, Educational Studies in Mathematics, Vol. 82, No. 1, pp 145-164. Roberts, N., and Butcher, N. (2009) ‘Evaluation of the imfundo yami/yethu project: Executive summary’. [Online]. Available: https://projects.developer.nokia.com/Momaths/wiki/sharinglessons [5 Feburary 2013]. Pachler, N., Bachmair, B., and Cook, J. (2010) Mobile learning: Structures, agency, practices, New York: Springer. Pierce, R., Stacey, K., & Barkatsas, A. (2007) ‘A scale for monitoring students’ attitudes to learning mathematics with technology’, Computers & Education, Vol. 48, No. 2, pp 285-300. Pouezevara, S., Dincer, A., Kipp, S., and Sariisik, Y. (Dec 2013). Turkey's FATIH project: A plan to conquer the digital divide or a technological leap of faith? Turkey: RTI International & Education Reform Initiative (ERI). Sawaya, S. F., and Putnam, R. T. (2015) ‘Using Mobile Devices to Connect Mathematics to Out-of-School Contexts’ in Traxler, J. and Crompton, H. (eds.) Mobile Learning and Mathematics, New York: Routledge. Shih, S.C., Kuo, B.C., and Liu, Y.L. (2012) ‘Adaptively ubiquitous learning in campus math path’, Educational Technology & Society, Vol. 15, No. 2, pp 298-308. Tapia, M. (1996). The Attitudes toward Mathematics Instrument, ERIC. Traxler, J. (2005) ‘Defining mobile learning’, International Conference on Mobile Learning, Qawra, Malta, pp 261-266. Vavoula, G. N., and Sharples, M. (2009) ‘Meeting the challenges in evaluating mobile learning: a 3-level evaluation framework’, International Journal of Mobile and Blended Learning, Vol. 1, No. 2, pp 54-75.