The effects of using computer maths games to develop functional numeracy skills with SEN students
Researched by Truong Dinh
INTRODUCTION
During the academic year of 2015-2016, the researcher was tutoring the able students who are young people aged 16-24yrs. The researcher’s focus is on ICT functional skills qualifications offered by the NCFE awarding body. Students are expected to develop their ICT skills using Microsoft Office. Students will learn how to set up formulas and create graphs on Excel. There is at least 20% of maths involved during the learning process.
The college, where the researcher is working, offers courses to students with learning difficulties. According to Special Educational Needs and Disability Code of Practice (GOV.UK 2015, p.15), “A child or young person has SEN if they have a learning difficulty or disability which calls for special educational provision to be made for him or her”. The researcher’s concern is how to help SEN students overcome anxiety with maths and encourage them to develop their numeracy skills so that they can use these skills in everyday life. It is hoped that when the students improve their maths skills they will be able to answer the Excel questions in their ICT assessments with more success.
During the planning stage, the researcher first decided to use ICT to help develop numeracy skills with SEN students. After consulting with his course tutors, the researcher narrowed down his research and focused on maths games in order to make it manageable. “Mathematical games prove highly engaging” (Ofsted Nov 2011, p.9). The central question of the project was “what are the effects of using computer maths games to help SEN students improve their numeracy skills in everyday life?”.
Other qualitative aspects related to the central question were:
a) “Can computer maths games help to encourage SEN students to learn maths?”
b) “How can the tutor show learning maths is taking place within the sessions?”
c) “How can the tutor provide evidence to highlight the numeracy development progression of their students?”
Another aspect was the Ofsted inspection framework. Ofsted insists that it is good practice to embed maths into other sessions. The purpose is to develop students’ “understanding and enjoyment of using mathematics in everyday life” (Ofsted Nov 2011, p.10). Functional maths is one of the researcher’s strong subjects which he outlined in a SWOT analysis. Based on it, the researcher set up the aims of his action research:
“Using computer maths games to help SEN students develop their numeracy skills in everyday life.”
A hypothesis was also constructed:
“Using a variety of computer maths games, aimed at students' individual levels, created to engage and motivate, this will improve their functional numeracy skills.”
During the investigation, the researcher carefully considered ethical issues such as informed consent and confidentiality. Stringer (2007, p.54) advises “As researchers we have a duty of care in relation to all people we engage in processes of investigation”. The consent forms and schedules were sent to students’ parents so that the parents would know what their children were involved in. The researcher also took into account the possibility of participants withdrawing from the project during the investigation period. “People have the right to refuse to participate, they may withdraw from the study at any time” (Stringer 2007, p.55).
ACTION RESEARCH THEORY
Action research is a systematic investigation tool to help the investigators implement and develop new strategies in teaching and learning. Carr & Kemmis (1986, p.162) describe:
“Action research is simply a form of self-reflective inquiry undertaken by participants in social situations in order to improve the rationality and justice of their own practices.”
The key figures on action research include Lewin, Stringer, Freire, McNiff and Whitehead. Lewin was credited as the first person who coined the term “action research”. Lewin found that the process of traditional research was unsatisfactory for further development. He introduced a new form of research which was based on people’s real-life experience. Lewin proclaimed that theories needed to have practical applications. “There is nothing so practical as a good theory” (Lewin 1951, p.169).
The concept of action research has been developed since then. One of the well-known researchers is Stringer who expanded Lewin’s ideas into the academic research fields in order to improve the performance of teaching and learning. McNiff & Whitehead have further enhanced it with practical guidance for the educational world.
This study was based on the framework of Stringer. The five steps of a sequence (Stringer 2008, p.5) which the researcher adapted consisted of designing, collecting data, analysing data, communicating outcomes and taking action. According to Stringer (2007, p.1),
“Action research is a systematic approach to investigation that enables people to find effective solutions to problems they confront in their everyday lives.”
The purpose of action research is to find better ways to solve a particular problem that emerges from collaborative work in which the researcher and participants are engaged. According to Wallace (2013, p.1), “Research is an essential tool for raising and maintaining the quality of learning and teaching”. It presents “an approach to inquiry that seeks not only to enrich professional practice but also to enhance the lives of those involved” (Stringer 2007, p.3). Evidence of effective teaching strategies is shown through learning. Stringer (2008, p.13) states it is “to provide educational practitioners with new knowledge and understanding, enabling them to improve educational practices”.
Action research also has negative aspects. It is argued that action research is just an enhanced form of reflective journal. The teacher who does both teaching and researching would easily create biases within the project. The project does not seem to be carried out perfectly as the teacher is not a full time professional investigator. Another critic is that action research is a continual process based on a particular situation therefore it should not be considered as a typical solution to be applied for all circumstances in the education sector. The solution on one specific project should not be re-used fully in other projects but has to be studied again through the cycles in order to obtain meaningful results for a particular problem.
LITERATURE REVIEW
During the planning stage, the researcher did a review on literature. “The researcher, at whatever level of experience, is expected to undertake a review of the literature in their field.” (Hart 2007, p.9). The article “Online and other ICTs applications for teaching math in special education” (2014, pp.45-53) by Drigas & Ioannis was used as a guideline. This paper outlined the needs to improve learning by using technologies aimed at students’ ability and age. The investigators came up with evidence on the effectiveness of using ICT to teach maths.
An Ofsted report (Apr 2011) was used: “Tackling the challenge of low numeracy skills in young people and adults”. This report presented how to tackle the challenge of low numeracy skills in young adults in 59 training colleges. The paper evaluated the numeracy skills programmes for post-16-year-olds and identified the challenges faced by most providers:
“The potential for the use of information technology was not exploited sufficiently in advancing learners’ practical application of numeracy skills.” (Ofsted Apr 2011, p.6)
There is a gap between the application of functional numeracy skills and the use of information technologies in teaching.
The researcher also found several journals which he could use. The relevant literatures would definitely “help to define the focus and scope of the research project about to be undertaken” (Gray 2014, p.6).
1) “Computer-assisted teaching and mathematical learning in Down syndrome children” (2006, pp.298-307) by Tudela & Ariza.
This paper explored computer-assisted teaching by carrying out the project on 70 children. These children were selected at average ages of 6.3-6.8yrs without severe health problems. The researchers adapted a special multimedia software for these children which focused on simple counting. One group used multimedia teaching and the other with traditional methods. Tudela et al. applied the comparison techniques of the mean scores and standard deviations for data analysis. The results showed that the group using computer-assisted teaching had a higher performance in maths than the other group. Tudela et al. (2006, p.305) concluded in their findings:
“It could be suggested that the computer, and more specifically the use of multimedia teaching programs, optimizes the learning of these concepts for people with Down syndrome.”
2) “Effectiveness of computer-assisted instruction on enhancing the classification skills in second-graders at risk for learning disabilities” (2010, pp.1115-1130) by Mohammed & Kanpolat.
This paper investigated on the effectiveness of using computer-assisted instruction. It had been done with 68 children who were at risk of learning disabilities with the mean age of 7.35yrs. These children were trained to use computer-assisted instruction to classify selected items. Mohammed et al. adapted the complex statistical techniques for data analysis. The results showed that the group who used computer-assisted instruction performed their classification skills better than another group who did not use assisted technologies. Mohammed et al. (2010, p.1126) concluded in their findings:
“Computer-assisted instruction should be used with children who are at risk of learning difficulties.”
3) “The effect of using computer games in teaching mathematics on developing the number sense of fourth-grade students” (2013, pp.1477-1482) by Nejem & Muhanna.
This paper focused on the effects of using computer games in teaching mathematics. It studied a sample of 81 students. Nejem et al. particularly focused on the number sense tests of complex fractions and used the methods of comparisons of the means for data analysis. The evidence showed that the experimental group achieved higher scores on the number sense tests than the control group. Nejem et al. (2013, p.1481) claimed in their findings:
“Computer games enhance the motivation of the students and draw their attention to learning mathematics by eliminating the elements of boredom that might occasionally face the students.”
All these publications mainly focused on child education and individual teaching methods. According to Piaget (1936), children and adults have “different cognitive abilities”. None of these papers mentioned the use of technologies for group teaching. The researchers did not consider mixed learning abilities within adult classes, behavioural challenges or high needs students. Moreover, these publications did not mention any involvement with students’ parents in the process of learning. The main purposes of this study were to attempt to narrow down these gaps and to promote the use of technologies in order to motivate SEN students to learn maths. It is hoped that the evidence-based study on this project will advance understanding of adult learning in the special education sector.
METHODOLOGY & TRIANGULATION
The researcher applied the theory of methodological triangulation to his action research project. “The credibility of a study is enhanced when multiple sources of information are incorporated.” (Stringer 2007, p.58). For gathering qualitative data, the researcher used the methods of observations, evidence of students’ work and interviews. For collecting quantitative data, the researcher used a variety of methods such as tests, quizzes, checklists and questionnaires. According to Hart (2007, p.28),
“One of the most important outcomes of the search and review will be the identification of methodological traditions which, in turn, will help to identify data-collection techniques that can be considered for use in the work.”
During the planning stage, the researcher carried out an initial interview with the experimental group. The researcher set up the questionnaire for all the tutors at the college and conducted constructive interviews with his students in order to seek the answers to the action research questions. The questionnaires and interviews which were set up combined both quantitative and qualitative methods by using closed and open questions. “It helps to balance out any of the potential weaknesses in each data collection method” (Gray 2014, p.37). The researcher implemented this during the action research process and acted as both tutor and investigator (“Teacher as Researcher” - Stenhouse 1979). The researcher adapted several methods to measure students’ skills during the investigation such as developmental questions, practical tests, quizzes, observations and peer tutoring.
During the monitoring stage, the researcher observed students and collected their work. When observing students the researcher kept a record of their performance by using a research diary (“Start a research diary as soon as you start your research” - Bell 2014, p.44). In order to obtain further support in learning, the researcher tried to involve students’ parents by asking students to do their homework with parents’ confirmation.
The researcher thought using the tactics of rewards and parents’ involvement would encourage students to learn maths.
The reflective models which the researcher used throughout his project were Brookfield’s critical lenses (1995) and Schön’s reflective practice (1986). The researcher has found that using these models effectively enabled him to reflect on his own practice more practically. “Looking in the mirror: Action research as reflective practice” (Wallace 2013, p.28). The researcher adapted several suitable theories of teaching and learning during the investigation such as Bloom’s taxonomy (1956), Bruner’s scaffolding concept (1976), Maslow’s motivation theory (1987) and Vygotsky’s zone of proximal development (1978).
The project was implemented with two cycles. Each cycle went through stages consisting of planning, acting, observing and reflecting. During cycle 1, the initial interview with the experimental group was carried out and had been recorded for reference.
When the project started, one participant withdrew and two others moved to two different groups, so the researcher asked another student to take part. There were 5 participants in the experimental group but were in 3 different groups. Four participants in the control group were also allocated ready for the pre-tests.
The researcher collected feedback from the experimental group throughout the project. Some were given verbally and some were sent by email. Several letters for homework were sent to the parents and merits were given to those students for their effort. One participant struggled with basic subtraction so the researcher modified the schedule and asked a volunteer to support her on a 1:1 basis. There was one participant who worked very hard during the project. During observations, the researcher noticed that her maths skills had improved significantly. The researcher revisited the schedule and set up challenging work for her. In the interview, she told the researcher that playing computer maths games helped to reduce her anxiety with maths and greatly improved her confidence. This might be due to the parents supporting her at home during the investigation period.
During cycle 2, one participant in the experimental group was sent out for work placement on the days she normally had the ICT sessions. So the researcher had to catch up with her whenever he had non-contact sessions. Apart from this, it was a successful cycle.
RESULTS
Table 1: Mean test scores for the experimental group (R = Correct answers)
On the means of the pre/post-tests, the experimental group scored 2.8 and 7.6 respectively using a written method (35% to 95%). By using a calculator, the mean scores were 5 and 7.8 (62.50% to 97.50%).
Table 2: Mean test scores for the control group
On the means of the pre/post-tests, the control group scored 2.5 and 2.75 respectively using a written method (31.25% to 34.38%). By using a calculator, the mean scores were 2 and 3 (25% to 37.50%).
Figure 1: Test scores for the experimental group using a written method
The line chart on Figure 1 showed that all participants in the experimental group performed better on the post-test using a written method, especially student A and E.
Figure 2: Test scores for the experimental group using a calculator
The line chart on Figure 2 showed that all participants in the experimental group performed better on the post-test using a calculator, especially student A D and E. Student B maintained a high score on both tests.
Figure 3: Test scores for the control group using a written method
The line chart on Figure 3 showed that student G and I performed slightly better on the post-test using a written method, but student F remained the same and student H slightly dropped down on the post-test.
Figure 4: Test scores for the control group using a calculator
The line chart on Figure 4 showed that student G made good improvement and student I performed slightly better using a calculator, but student F and H did not make any progress on the post-test.
Figure 5: Column chart of the means for the experimental group
The column chart on Figure 5 showed that the means of the test scores for the experimental group at pre/post stages increased from 2.8 to 7.6 using a written method and from 5 to 7.8 using a calculator.
Figure 6: Column chart of the means for the control group
The column chart on Figure 6 showed that the means of the test scores for the control group at pre/post stages increased from 2.5 to 2.75 using a written method and from 2 to 3 using a calculator.
The results on both methods showed that the experimental group achieved better outcomes than the control group who did not use the system of computer maths games.
DISCUSSION
From the pre-test using a written method shown on Table 1 for the experimental group, student B C and D did well and scored 87.50%, 37.50% and 50% with the correct answers of 7, 3 and 4 respectively.
On the post-test using a written method, all participants in the experimental group achieved good results with scores between 87.50% and 100%. Student A showed a significant improvement from 8 wrongs on the pre-test to 7 corrects on the post-test, scored 87.50%. Student E was even better showing an excellent outcome scored 100% from 8 wrongs on the pre-test to 8 corrects on the post-test. Student B managed to get all the answers correctly on the post-test. The results on the post-test using a written method showed an improvement with the experimental group.
During the tests, participants used a calculator to check the results. They did well with high scores of percentages. Student A and D showed good performance from 4 corrects to 7 and 8 corrects respectively. Especially, student E achieved excellent results from 3 corrects on the pre-test to 8 corrects on the post-test (37.50% to 100%). Student C also made good progress from 6 corrects on the pre-test to 8 corrects on the post-test and achieved a score of 100%. Student B showed good confidence in using a calculator throughout the project (100%).
From the pre-test using a written method shown on Table 2 for the control group, student F G and I had a score of 25% each whereas student H had a highest score of 50% with 4 correct answers. On the post-test, student G and I achieved good performance with 3 correct answers scored 37.50%. Student F managed to get a score of 25%. Student H dropped down from 50% to 37.50% with only 3 correct answers on the post-test.
On the pre-test using a calculator, student H gained a score of 50%. Student G struggled on the pre-test but performed better on the post-test with 3 corrects scored 37.50%. Student F managed to get 2 corrects on both tests with a score of 25%. Student H maintained a score of 50% on both tests using a calculator. Student I achieved better outcomes with 3 corrects on the post-test (37.50%).
Mean 1: Based on the literature reviews, the researcher used a similar technique to work out the means of the test scores.
The means using a written method for the control group showed that the average performance was slightly improved (10% increased). The main reasons are both G and I made good improvement from 25% on the pre-test to 37.50% on the post-test. The means using a calculator for the control group showed that the average performance was evidently improved (50% increased). The main reasons are both G and I achieved better outcomes on the post-test (37.50%).
The means using a written method for the experimental group showed that the average performance was significantly improved (171% increased). The main reasons are both A and E made significant improvement to 87.50% and 100% on the post-test respectively. The means using a calculator for the experimental group showed that the average performance was evidently improved (56% increased). The main reasons are student A D and E made good improvement on the post-tests.
There was evidence to prove that the experimental group achieved better outcomes than the control group who did not use digital maths games in their studies.
Mean 2: During week 5, participants in the experimental group were given £2 each to spend at the college’s tuck shop. They were required to work out the change using both methods.
1 = Work out the change correctly 0 = Not work out the change correctly
Student A and E struggled working out the change using a written method on both practice and test papers. Student D did well on practice but struggled when doing the real test using a written method. Based on the total group score using a written method, participants performed better on the practice test than the real test, with the mean of 0.6 compared to 0.4. In using a calculator, all participants did well with 5 corrects out of 5 on both practice and test papers.
Figure 7: Column chart of the means (Tuck shop)
Other methods of surveys and interviews were carried out for implementing different views of data analysis. “Incorporating analysis from diverse sources provides the basis for greater understanding and the formulation of effective solutions to the research problem” (Stringer 2008, p.119). Staff surveys were set up for all the tutors at the college. Most of the subjects in which the tutors found easy to embed maths include cooking, music, photography, practical projects, functional skills and ICT. But some other optional subjects such as drama and circus skills it was a challenge as the tutors found it difficult to embed. Several tutors in vocational subjects pointed out that embedding maths should not be overdone otherwise it would outweigh the contents of other teaching subjects.
On the fifth week of action research, the surveys were carried out with the experimental group.
One student did not like to play maths games on the computer or play maths games in the ICT sessions. Four others agreed.
One student did not agree that playing maths games could help to reduce maths anxiety. One student did not struggle with maths anxiety. Three others agreed.
One student gave a low score of 4 points for learning maths with computer maths games. Two students gave a high score of 5 points and two others gave a top score of 6 points.
One student disagreed on question 8 and 9. The reason is that the maths games which the researcher set for him in the first cycle were too easy. However, he agreed on question 5, 6 and 7. He told the researcher in the interview that playing maths games on the computer was a good idea for learning maths.
Another student commented on question 10 that she liked playing challenging maths games as she has built up her confidence since then. Her maths skills significantly improved and her anxiety with maths seemed to reduce recently. Three others agreed that playing computer maths games was fun and they enjoyed learning maths.
During the study, the researcher carried out two stages of interviews with students. The first stage was a group interview which was carried out before starting the project. Through the initial interview, the researcher had learnt how students felt about maths, what encouraged them to learn maths and how they wanted to learn maths. Most of them liked to learn maths and ICT together in their normal ICT sessions. However, there were disadvantages in group interviews as some less able students were easily influenced by others’ views. The second stage of interviews was completed on an individual basis. Most of them liked to do it at the starter activity. They found that playing maths games was fun and encouraged them to learn maths. They liked learning it in a competitive way.
All participants agreed that this was an effective way to learn maths as it helped them remember more of what they have learnt. Playing functional maths games helped them concentrate on the tasks more and they understood that they could use it in their everyday life. Students preferred the learning schedule to be organised in advance so that they could practise it at home. All participants liked the ideas of using computer maths games to learn maths and ICT together in a fun and competitive way.
However, the work which the researcher set up only studied a small sample of the population (10%) and mainly focused on money aspects. The sessions were limited once a week for 80 minutes and only carried out over six weeks. The games from the sites were not fully designed for adults. The flash games were only available for PCs. The activities mainly relied on the sites and Internet. Two groups of participants selected were not perfectly matched in terms of specific learning abilities and levels. One participant in the experimental group did not have a computer at home. The quantitative techniques used for data analysis were too simple.
RECOMMENDATIONS
The researcher has realised that action research is “a form of self-reflective practice” (McNiff 2002, p.6) and is a continual process for the development of effective teaching and learning. “Action research is a work in progress.” (Brydon-Miller et al. 2003, p.11). Therefore, this project should not be considered as the final one to generalise the whole case of SEN students at the college. This would need to consider as an initial action research on a particular group. In the near future, the researcher will develop further research with larger sampling groups over longer period of times to provide additional evidence.
However, as this project was carried out successfully and the hypothesis was systematically proved in some ways. So the researcher is planning to adapt these strategies for ICT sessions and will use them as starter activities or competitive quizzes after session plenary. Other subject tutors at the college are recommended to adapt these strategies for group activities in order to help develop students’ numeracy skills in a competitive way. This is fun and exciting, encouraging students to focus on their tasks. Achievable quizzes are easily set up. Students are encouraged to self-assess their own work using score sheets. Scaffolding approach is adapted to help less able students. Differentiated activities are carried out to develop individual students’ skills. Peer tutoring and supportive feedback are used to build up students’ confidence. These competitive strategies could assist students’ autonomy in learning throughout their courses at the college.
Truong Dinh, BSc QTLS
ICT Tutor - Specialist College
