Students as Partners in Research and Assessment

Students as Partners in Research and Assessment An Applied Reflection from a Level 5 Research Skills Module Dr Andrew Clegg Principal Lecturer Learning and Teaching Programme Co-ordinator for Tourism Management

[HEA, 2014]

Student Partnership

Aims  To contextualise the provision of research skills at Level 5  To highlight results from longitudinal analysis looking at student anxiety to statistics  To discuss how this research has informed pedagogic practice and a focus on partnership

“

I have always had a fear of numbers and maths has never been a strong subject of mine’ [Student Feedback]

“

I find maths difficult and always found it hard to cope with, it worries me I won’t be able to keep up and understand the content of the module’ [Student Feedback]

LEARNING OUTCOMES

Context: BML224 Data Analysis for Research  Relate and critically apply the use of quantitative

methodologies to their own research  Distinguish between the characteristics of different data

types and apply to quantitative methodologies and data collection strategies  Acquire, analyse, interpret and present quantitative

data appropriately using SPSS and Excel  Accurately select and apply appropriate advanced

statistical techniques in SPSS and analyse the output accordingly  Relate underlying statistical theory, such as the normal

distribution, to statistical analysis

CONTENT

Context: BML224 Data Analysis for Research  Introduction

 Research Design and Data Collection  Exploratory Data Analysis 1 - Basic Descriptive Statistics  Exploratory Data Analysis 2 - Presenting Data  Normal Distribution and Patterns of Dispersion  Looking for Difference: Student T-Test and Paired

Samples T-Test  Looking for Difference: Mann Whitney and Wilcoxon  Looking for Difference: Chi-Squared  Looking for Association: Correlation

Year of Entry

Maths GCSE (% of those with known results)* A

B

C

D

E

C to E

2007/08

8%

48%

43%

0%

3%

46.0%

2008/09

9%

28%

60%

2%

0%

62.0%

2009/10

12%

38%

49%

1%

0%

50.0%

2010/11

7.7%

30.8%

58.8%

1.9%

1.9%

62.6%

2011/12

14.0%

48.4%

35.5%

0.0%

2.2%

37.6%

2012/13

20.4%

37.2%

40.7%

0.9%

0%

41.6%

2013/14

18.9%

33.3%

42.4%

4.5%

0.8%

47.7%

2014/15

16.5%

35.1%

46.4%

1.0%

1.0%

48.5%

2015/16

20.3%

31.5%

41.9%

2.7%

0.0%

44.6%

2016/17

26.2%

28.6%

42.9%

2.4%

0.0%

45.2%

2017/18

10.6%

25.5%

55.3%

4.3%

2.1%

61.7%

[*Figures exclude international applications]

Tackling Transition

Tackling Transition

Student Attitudes to Statistics  A review of the available literature reveals a common and

persistent theme:  High levels of anxiety... ‘for many students statistics is perhaps the

most anxiety-provoking, difficult, or critical subject within their courses of study’ (Baharun & Porter, 2009)  ‘Statistics courses are viewed by most students as an obstacle

standing in the way of attaining their desired degree’ (Perney and Ravid, 1991)  ‘While the material covered, the level of difficultly, and the approach

vary enormously, most have one aspect in common: the course is typically the most unpopular in the academic programme’ (Keller et al, 1988)

Student Attitudes to Statistics  Statistics = Maths  Problems of contextualisation – where, why and how does

it fit in and relate to their degree/career?  Coping strategy – failure is a foregone conclusion

therefore students accept low grade in a statistics module and recoup elsewhere – priority is a pass mark

Pre-Module Survey  Section 1: Student Profile - profile information and initial

confidence level starting the module  Section 2: Experience and Competency - competency

levels around the use of key statistical approaches/techniques and use of related software (e.g.

Excel)  Section 3: Attitudes Towards Statistics - attitudes

towards statistics and factors influencing their own perception/level of anxiety

SUMMARY ‘How confident are you about

starting this module?’

VERY CONFIDENT VERY ANXIOUS 2% 5% QUITE ANXIOUS QUITE CONFIDENT 9% 8%

CONFIDENT 12% ANXIOUS 22%

Anxious to Very Anxious

75% Uncertain to Very Anxious

UNCERTAIN 42%

2010/11-2016/17

“

33%

I am not mathematical and hate working with numbers. I try and avoid it as much as I can’ [Student Feedback]

25% Confident to Very Confident

CONFIDENCE LEVEL 2010/11-2016/17

“

Statistics, numbers and maths scare me!’ [Student Feedback]

45.5% Very Anxious to Anxious

86.7% Very Anxious to Uncertain

Female

Male

CONFIDENCE LEVEL BY GENDER 2010/11-2016/17

21.9% Very Anxious to Anxious

64.9% Very Anxious to Uncertain

13.3%

35.1%

Confident to Very Confident

Confident to Very Confident

COMPETENCY LEVELS – USING A PERCENTAGE HAVE HEARD OF BUT NEVER USED 1%

NEVER HEARD OF 1%

HAVE HEARD OF BUT CANNOT USE/APPLY CONFIDENTLY 21%

23% never heard of, never used or cannot apply a percentage

HAVE HEARD OF AND CAN USE/APPLY CONFIDENTLY 77%

COMPETENCY LEVELS – CALCULATING AN AVERAGE HAVE HEARD OF BUT NEVER USED 1%

NEVER HEARD OF 1%

HAVE HEARD OF BUT CANNOT USE/APPLY CONFIDENTLY 21%

23% never heard of, never used or cannot apply an average

HAVE HEARD OF AND CAN USE/APPLY CONFIDENTLY 77%

COMPETENCY LEVELS – CROSSTABS HAVE HEARD OF AND CAN USE/APPLY CONFIDENTLY 2%

NEVER HEARD OF 69%

84% never heard of, never used or cannot apply a crosstab

HAVE HEARD OF BUT CANNOT USE/APPLY CONFIDENTLY 13%

HAVE HEARD OF BUT NEVER USED 16%

“

PASSING IS MY MAIN GOAL FOR THE MODULE’

100% 9.7% 90% 80%

20.2%

70% 60%

14.5%

STRONGLY DISAGREE DISAGREE

50% NO OPINION 40%

31.3% AGREE

55.6% Agree or Strongly Agree

30% STRONGLY AGREE

20% 10% 0%

24.3%

“

I AM WORRIED ABOUT THIS MODULE BRINGING DOWN MY AVERAGE GRADE FOR THE SECOND YEAR’

100% 9.2% 90% 80%

24.3%

70% 60%

STRONGLY DISAGREE 17.7%

DISAGREE

50% NO OPINION 40% 28%

48.8% Agree or Strongly Agree

AGREE

30% STRONGLY AGREE

20% 10% 0%

20.8%

“

I AM WORRIED ABOUT TAKING THIS STATS MODULE AS MY MATHS ABILITY IS LOW’

100% 90%

13.8%

80% 70%

34.4%

60%

STRONGLY DISAGREE DISAGREE

50% 15.1%

NO OPINION

40% AGREE

36.8% Agree or Strongly Agree

30% 20.4% 20% 10% 0%

16.4%

STRONGLY AGREE

AREAS OF ANXIETY – TOP FIVE 70

Percentage Respondents (%)

60

50

Not Anxious 40

Slight Anxious

30

Anxious to Very Anxious

20

Don't Know

10

0

TAKING EXAMS IN THIS MODULE

APPLYING USING COMPUTER STATISTICAL PACKAGES TO TECHNIQUES TO REAL ANALYSE WORLD SITUATIOS INFORMATION

FORMULATING AND TESTING RESEARCH HYPOTHESES

UNDERSTANDING STATISTICAL PRINCIPLES

AREAS OF ANXIETY – TOP FIVE 70

Percentage Respondents (%)

60

50

Not Anxious 40

Slight Anxious

30

Anxious to Very Anxious

20

Don't Know

10

0

TAKING EXAMS IN THIS MODULE

APPLYING USING COMPUTER STATISTICAL PACKAGES TO TECHNIQUES TO REAL ANALYSE WORLD SITUATIOS INFORMATION

FORMULATING AND TESTING RESEARCH HYPOTHESES

UNDERSTANDING STATISTICAL PRINCIPLES

Implications for pedagogy

“

STATISTICS IS NOT THE SAME AS MATHS AND I AM APPROACHING THIS MODULE WITH AN OPEN MIND’

100%

1.8% 6.6%

90% 80%

27.5%

70%

STRONGLY DISAGREE

60%

DISAGREE

50% NO OPINION 40%

45.1% AGREE

64.1% Agree or Strongly Agree

30% STRONGLY AGREE

20% 10% 0%

19%

Assessment Regime Year

Assessment Regime

2010-2011

Practical portfolio and exam

2011-2012

Practical portfolio and exam

2012-2013

Live research project and in-class practical

2013-2014

Live research project and in-class practical

2014-2015

Live research project and in-class practical

2015-2016*

Live research project, presentation of results and defense of poster

2016-2017*

Live research project, presentation of results and defense of poster

2017-2018*

Live research project and defense of poster

*Incorporating peer assessment

Live Research Project

Objective 2: Security

Objective 1: Usability and Availability The first objective focuses on the usability and availability of online banking applications.

The aim of this objective was to determine the level of availability amongst students and their ease of use. The survey looked at the facilities offered by online banking websites and applications. From this it was determined which various functions require improvement or development.

The discovery was in some areas there was a distinct difference in the reality of use in comparison with expectation, within the majority of the various banks, which required improvement. Other functions had minor differences, as details in Figure 4.

Of all the respondents, 3.8% used a website to access their banking, as opposed to 96.2% which used an app. From this, it was decided that the usability of the ‘app’ (Question 14.b) was the most relevant for analysis. The charts below show 9 different functions offered by the app.

This poster will critically analyse the drivers and barriers of online banking that students at the University of Chichester have. The research has been divided the research into 3 objectives to reach a conclusion where recommendations are made. The research objectives are:

1 Ease of transferring money between accounts

Literature Review

2

2

3

4

5

4

5

4

5

1

3

4

5

3

4

5

• Personal innovativeness

According to Google Trends, Online Banking was at the height of interest in late 2008 when popularity increased due to curiosity, and ‘following the crowd’, reinforcing the social norms theory. Question 17 looks Timeline 1: https://trends.google.com/trends/explore?date=all&q=online%20banking at the opinions of students in the UK and what leads them to use online banking on a ranked scale.

The increased availability of online banking has made it easier for people to access their accounts at any location and any time (Laukkanen, 2007). This guided the survey looks at the frequency of use of online banking, as well as what it is used for. Wan et al. (2005) states that online banking is not ready to carry the burden of all banking needs, and people still require to physical bank to fulfil their needs. Following this, Question 20 was adapted to gain the opinions of students and how much they depend on the physical presence.

Security is a major concern in online banking and can deter people from using it. Masrek et al. (2014) looked at the relationship between technology and trust, with mobile banking satisfaction and reliability. This journal’s findings in Malaysia found a correlation which provoked Question 23, where students were asked to state whether they trusted various virtual platforms and equipment. Concerns with security result in increased use of passwords, but this can have set backs, as the Ponemon Institute LLC (2013) maintains the belief that humans are generally forgetful. Students were therefore asked various questions based on their failures to complete online banking actions.

Following the research conducted, appropriate questions were formulated to provide a response to the research objectives, questioning availability, usability and security, enabling an educated recommendation to the most efficient banking provider based on the experiences of students in the UK.

2

3

4

5

3

4

5

20 18 16

66.7% of respondents were female, compared to only 31.5% which were male, as illustrated in Figure 2. The remaining percentage opted to remain anonymous.

Frequency

14 12 10 8 6 4 2 0 18

19

20

21

22

23

24

25

30

35

39

Age

The sample selection was students of University of Chichester, and the survey was distributed via University emails and social media such as sports teams, Facebook groups and similar University pages. Due to this sample, 66.7% of respondents were aged 19-21. Full details in Figure 1.

Figure 2: Gender of Respondents

Figure 3: Primary Bank used by Respondents Santander 22%

Other 26%

HSBC 15% Barclays 15% NatWest 4% Nationwide 18%

1

2

1

3

4

5

3

4

5

The above information is useful in determining the best functions of online banking apps and where they seem to lack in usability. Interestingly, checking the balance of your account is the only function offered by an online banking app that surpasses the expectations of its customers. In this case, the expectation average was a rating of 4.6 and in reality was ranked 4.73. However, there were a few larger gaps between expectation and reality. The three largest gaps were as follows: Managing Direct Debits Applying for overdraft and extensions Opening a new account

50

Recommendations

40

The recommendations have been made as if a new group were researching the same objective using similar data collection methods which lead on from our findings.

Focusing on people who primarily do not use online banking instead of students who do would enable more recommendations to be made to banks. It would explain the barriers against using online banking on a wider scale as most students currently bank online so it caused a limitation in our research as only 1 person did not use online banking.

0 Yes

No

Yes

Santander (12)

No

H SBC (8)

1. Nat West

It is clear that the above areas are the most in need of improvement with regards to online banking apps in order to fulfil the expectations of its customers.

User Competency for the above Functions Question 14.b.i. looked at the percentage of users that felt they could or could not competently complete all of the above functions. This was cross referenced with which banks respondents used to give an idea of which banks users are more confident and competent in completing various functions, details in Figure 5.

Figure 5: Competency in Completely Various Online Banking Functions 100 90 80 70 60 50

Yes

No

NatW est (2)

Yes

No

Nationwide (10)

2. HSBC

Yes

No

Barclays (8)

Yes

No

In order to get a larger sample size and gather professional’s opinion from the banks, the project should be completed over a larger timespan in order to allow more responses and further collection of qualitative data. This would include using the extra time to conduct a focus group or an interview.

O ther (14)

With the exception of NatWest which only had 2 respondents, users of Santander answered the question as ‘never’ the most frequently in regards to technological issues with 25%.

3. Barclays

These banks could therefore potentially be less secure than the others with fraudulent activity being higher. Although NatWest is included in this top ranking, they only had 2 respondents meaning it is not a fair sample to make recommendations to.

Figure 8: Failure to Log On From the survey, it is evident that respondents trust their banks regarding their security, however it has shown that it can have a negative effect on the usability of online banking. Question 21 states that three common causes of the failure to complete an online transaction are as below. 52.6% of the total respondents have security related issues when failing to complete a transaction.

•

Forgotten password (26.8%)

•

Forgotten answer to security question (18.6%)

•

Forgotten username (7.2%)

Maintenance Shutdown to App 23.7%

HSBC scored highly for those respondents that said they sometimes have technological issues with 50% saying sometimes and 50% saying rarely. HSBC scored the highest in the top 2 categories for the worst performance. Overall, Barclays and NatWest seemed to have the fewest technological issues and would be the most reliable bank in the logistics department.

Figure 11: Failure to Access due to App Maintenance

Security Measures

100 Forgotten Password 26.8%

90 80 70 60

Maintenance Shutdown on Website 14.4%

Website Glitches 9.3%

40

Forgotten Username 7.2%

30 20

0 Yes

No

Santander (12)

Yes

No

HSBC (8)

Yes

No

NatW est (2)

Yes

No

Nationwide (10)

Yes

No

Barclays (8)

Yes

No

Other (14)

The number next to each of the banks names shows the frequency of respondents that used this bank.

Being locked out of site for a set time (44%)

•

Lengthy password reset process (34%)

Mobile Payment Systems

Removing those results of the users of “Other” banks, the graph shows Santander and Nationwide users felt far more confident is using their banking apps than NatWest, HSBC and Barclays customers. Only 2 respondents used NatWest so this statistic does not give a broad perspective, however, a higher percentage of those at NatWest felt they were competent, compared to Barclays and HSBC.

Yes 60.4%

Customer Attitudes Question 17 asked participants about what affects their attitudes towards online banking. Mohammadi (2015) found each of the four causes to carry an even weight when it came to influencing opinions, however, from our research, we found that students are most affected by ‘Ease of Use’ at 88% and ‘Usefulness’ at 89% ranking the top two most relevant.

Figure 6: Customer Attitudes There is little concern for‘ Personal

In the last 3 years, the interest in online banking has been at a steady pace, see Timeline 1, and people are less concerned with the ‘hype’ of online banking. The student respondents show that they are less interested in social trends influencing their attitudes, and are more attracted to a system that is going to be easy to use, as well as fit for purpose.

Respondents were asked whether they use ApplePay or similar applications such as AndroidPay: No 39.6%

The people who use Apple Pay or similar, trusted the security of the technology more than those who stated they don’t use it. This is supported by the mean ratings out of 5 below.

Yes — 3.84 out of 5

References

0 Santander (12)

HSBC (8)

NatW est (2)

Nationwide (10)

Barclays (8)

Other (14)

•

Chaouali, W., Souiden, N. and Ladhari, R. (2017). Explaining adoption of mobile banking with the theory of trying, general self-confidence, and cynicism. Journal of Retailing and Consumer Services, 35, pp.57-67.

•

Masrek, M., Mohamed, I., Daud, N. and Omar, N. (2014). Technology Trust and Mobile Banking Satisfaction: A Case of Malaysian Consumers. Procedia - Social and Behavioural Sciences, 129, pp.53-58.

•

Shaikh et al. (2015) in: Muñoz-Leiva, F., Climent-Climent, S. and Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), pp.25-38.

•

Laukkanen (2007) in: Muñoz-Leiva, F., Climent-Climent, S. and Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), pp.25-38.

•

Mohammadi, H. (2015). A study of mobile banking loyalty in Iran. Computers in Human Behaviour, 44, pp.35-47.

•

Ponemon Institute LLC (2013). Moving Beyond Passwords: Consumer Attitudes on Online Authentication. A Study of US, UK and German Consumers. Nok Nok Labs, Inc.

•

Wan, W., Luk, C. and Chow, C. (2005). Customers' adoption of banking channels in Hong Kong. International Journal of Bank Marketing, 23(3), pp.255-272.

•

Google Trends. (2018). Google Trends. [online] Available at: https://trends.google.com/trends/explore? date=all&q=online%20banking [Accessed 30 Apr. 2018].

•

Montazemi, A. and Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A metaanalytic structural equation modelling study. Information & Management, 52(2), pp.210-226.

Figure 11, extracted from Question 21, goes into more depth from what was found on Figure 8.

These consequences would effect the availability of the service as the user is unable to utilise the full use of their account for a period of time. In question 23 the effect of these security measures on usability can be shown to deter 53.8% of respondents in which they discontinue the transaction. This suggests that these measures need to be streamlined which could have a negative effect on how secure users accounts are.

Of the users that selected “Other” as their bank, 100% felt that they could competently complete all of the functions. This is surprising as 74.1% of our respondents used one of the 5 named banks and yet none of these banks had a 100% competence rate.

Evaluation The groups research methods and data sample have been evaluated in order to discuss what would be different if this research project was to be completed a second time. Letters were sent to local banks to allow us to get an insiders perspective on the usefulness and usability of online banking. Unfortunately, there were no responses even though 10 letters were sent out. In order to ensure a response from a bank manager, the group could have gone into the bank and asked questions such as “did you receive our letter?” And “could you spare 5 minutes of your time now/later today to discuss online banking with us?”

Having the contrast of a professional’s opinion and students would be useful to compare whether the importance of transactions are different and whether the expectation vs. reality of completing these are also different.

Our sample size of 54 students was gathered from University sports pages, emailing the survey link to class members and asking friends. To maximise this sample size, a shorter questionnaire could have been used. Also an incentive such as a Costa voucher or an alcoholic beverage in the Student Union to entice more students. Questions such as “have you been a victim of fraud” would more than likely have a wider spread result as at the moment there is 2 “yes” answers and 52 “no”. A shorter questionnaire could be used to entice a larger sample size. In order to collect more data, we could have carried out a focus group with 6-8 people. This is to get more specific answers to questions as we can ask questions such as “can you elaborate on that” or “how you would feel if your bank made this change…”

10

Respondents were asked what the most frequent security problems they encounter are: •

50 40

Forgotten Answer to Security Question 18.6%

Consequences

20

Montazemi et al.’s (2015) meta-analysis categorises the innovation of online banking as two things: preadoption and post-adoption. Question 17 also reinforces the idea that Students are in the post-adoption phase as they are said to have a higher likelihood of acceptance which attention to innovation in usefulness and ease.

When constructing the survey, the overall opinion was that it would be common to know of or have been a victim of fraudulent activity. The results show the opposite with only 17.3% of respondents being a victim and 4 knowing of someone. Out of these 4 people, only 2 people said it had a negative impact on their opinion of banking online. The consensus was that it would have been a higher percentage due to Montazemi, A. and Qahri-Saremi, H (2015) describing trust as a deterrent of use.

Banks with the highest amount of fraudulent activity:

0.85 Gap 0.83 Gap 0.96 Gap

Question 8 asked is respondents if they use online banking with only 1 respondent out of the 54, answering no. This reinforces the fact that the use of online banking has become a ‘subjective norm’ amongst students as Mohammadi (2015) states. Despite later on at question 17 where 27% of respondents said ‘subjective norms’ does not affect their attitudes to online banking.

60

30

2

In order to conclude this research project, we had to summarise the results, make recommendations to someone else who would be carrying out this project and evaluate how the group constructed the project.

Concluding the results meant viewing how different the literature was to our findings. These differences have been analysed throughout the poster and below. In order to recommend changes to someone else if they took over our project, the idea of unlimited resources was used. For example completing the project over a larger time span. Evaluating how the group constructed the project meant making it apparent what we would do differently in order to enhance the project such as using other data collection methods.

Wan et al (2005) says online banking is not ready to fulfil all banking needs thus respondents were asked to either agree or disagree with the following statement, “all banking transactions can be completed online, and soon all physical could be obsolete.” 42.3% of respondents answered agree or strongly agree.

70

10

Innovativeness’ with 35% in the two most relevant or following ‘Norms’ with least having only 27% in the top two categories.

5 banks were chosen as the key areas for comparison. These banks are the most popular on the high street, and offer online banking services worldwide. 74% of respondents used one or more of these 5 banks. This was our expected response and allows us to determine the best and worse features offered by these banks. Full statistics in Figure 3.

Figure 10 shows how often users were unable to complete a transaction.

90

Opening a new account

10

The survey received a total of 54 responses.

These respondents used a variety of banking providers for different purposes which provided a range of data.

Figure 1: Age of Respondents

Question 20 helps to determine how often our respondents were unable to complete an online transaction due to personal or technological failure with their primary banking provider.

80

2

30

Data Set

With regards to usability, in Figure 5 the graph showed that Santander and Nationwide users felt far more confident in completing certain functions when compared to Barclays and HSBC customers.

100

2

1

Applying for overdraft and extensions

2

To determine the most efficient banking network to support the users requirements we broke the requirements down into the areas of usability, availability and security. A combination of these areas offer an idea as to the most efficient banking network and show areas that other banks have the potential to improve on.

20

Percentage

• Subjective norms

Mohammadi found each stimuli to have equal significance and positive influence amongst users in Iran, particularly in relation to social stimuli with ‘subjective norms’.

1

By using the information and results gathered from objective 1 and 2, along with other questions from the survey it is possible to determine which banking network was leading on usability, availability and security.

From this, is also then possible to determine the areas most needed for improvement.

Managing direct debits

Ease of finding a nearby branch

1

The purpose of this objective was to determine the most efficient banking network based on the requirements of their users.

Figure 10: Technological Issues

Figure 7: Victims on Fraud

Using the live chat function

3

3

Ease of paying others

To assist with the development of the survey, the group conducted secondary research, looking into previous studies and journals from various countries in order to develop quantitative and qualitative questions that answered the chosen research objectives. Shaikh et al. (2015) looked at the ‘rapid’ growth in popularity in the use on online banking with websites and mobile applications which influenced the first objective with attention to usability which is evaluated in Question 14 where participants were asked to rate their expectation of ease of use, in comparison with the reality. A study conducted by Mohammadi (2015) found that there were 4 key factors that affected customer attitudes to online banking which are: • Usefulness

2

Reality

Ease of checking online statements

• Ease of use

Figure 7 shows how many of the respondents have been a victim of fraud, the graph shows that many of the respondents (83.7%) have not personally been the victim of fraud. This shows that overall the banks are secure and take necessary actions to stop fraudulent activities from happening.

Ease of checking balance

Expectation

1

The results of question 18.1 where 50 respondents (96.2%) have stated that they trust their banks security where as only 2 respondents (3.8%) have said they do not. Information from our survey shows that 92% of respondents believe that their banking app is secure, compared to the 8% that did not. This 8% could be part of the respondents who have been a victim of fraud and are hesitant towards the app’s security. Montazemi et al.’s (2015) study suggests that “trust is an antecedent of intention to use.” This is why 96.2% of our respondents use an app compared to the 3.8% of them who use a website because the app’s security is trusted.

Fraudulent Activity

Respondents were asked to rate how easy they think it should be to complete a certain function in comparison with how easy it actually is. If a rating of 5 was given this means that it should be or is extremely easy to do and a rating of 1 means it should be or is very difficult to do.

Figure 4: Application Functions — Expectations vs Reality

1

Trusting Bank Security

Percentage

Introduction and Objectives

Conclusion

Objective 3: Recommendations on Efficiency

This section has information collected from the following questions: 6, 13, 18.1, 18.6a, 21, 22, 23, 27, 31, 32. This objective analyses banks security, with a focus on how it affects their user engagement.

Percentage

User Engagement: Drivers and Barriers for Students using Online Banking

No — 2.80 out of 5

Due to respondents primarily using the app, for the purpose of accessibility the graph shows the percentage of users from each bank that said they often failed to access the app due to system maintenance.

It is clear from the graph that NatWest, Nationwide and Barclays had a high percentage of respondents that experience maintenance problems. 100% of NatWest users who responded faced issues, along with 70% of those with Nationwide.

This data is important as 96.2% of users use banking apps as the sole location for their banking activities, therefore being able to see where improvements could be made to prevent potential customers going elsewhere is beneficial to businesses, but equally, customers can see that NatWest has the most efficient system.

Figure 12: Failure to Access Account

Figure 12 is taken from the results of Question 23, which relates to Question 21 detailing the various consequences of the failure issues shown in Figure 8. These consequences were:

Figure 9: Trust Question 32 asked respondents on a scale of 1-5 (1 being extremely unsafe) and (5 being extremely safe) how secure do they believe mobile payment systems such as Apple Pay to be.

As seen from our results in Figure 9, the majority of people (40.4%) scored their trust for these payment systems as 3. A 3 represents no opinion showing respondents are uncertain about the payment method. This may be because of its only recent increase in use or the fact they believe it is easier to just use a debit card as all respondents do have a debit account. On the other hand, 33.6% of participants stated that they do not use the mobile payment services thus, not joining the times. 3 years ago when these services became apparent, Barclays refused to use the system.

No 46% Yes 54%

•

Locked out of site for a set time

•

Lengthy password reset process

•

Additional passwords required

•

Blocked account

The responses show the percentage of users that said they would deter from completing their transaction due to the above problems.

It can be seen that the majority of respondents would give up on what they were doing due to their inability to complete a transaction, with 28 participants answering ‘Yes’ Vs. 24 which said ‘No’.

For the banks to be able to improve their availability and help customers to efficiently complete transactions, the consequences of the failure to complete the transaction clearly would benefit from being an easier process.

If customers are deterring from completing transactions due to the consequences of technical issues then these banks are effectively losing business and failing to provide an easy to use and efficient service.

The Star Bankers 1607882 1607872 1503267 1502497 1605214

Assessment Criteria

Poster Structure

 Evidence of clear research aims and objectives informed by background research

and supporting guidance brief  Clear and logical structure of the poster demonstrating progression against the

identified research objectives and links to underpinning research philosophies  Inclusion and justification for the appropriate use of qualitative and/or quantitative

methodologies in the research process  Clear extrapolation of answers and analysis based on the use of the appropriate use

of either qualitative or quantitative approaches (e.g. SPSS)  Ability to present results both visually and verbally accurately, succinctly and to a high

standard using appropriate formats and referencing conventions  Quality of the demonstrated critical reflection of chosen research methodology and

results as part of the ‘live marking’ and dialog with the module tutor(s) as outlined in the supporting guidance brief  Evidence of effective team working and engagement judged against specific peer

assessment criteria outlined in the supporting guidance brief

Assessment Criteria

Assessment Criteria

Students complete criteria sheet and grade their work prior to the marking event

Peer Assessment

Completed mid-point and after the marking event

Staff Moderation particularly liked the presentations “ Iwhich the students undertook. I was particularly impressed by the academic dialogue in BML246 which took place between the two tutors when discussing what mark should be attributed to a poster presentation.

This was excellent and worthy of wider dissemination across the School and wider University’

Outcomes – Grade Profile

Outcomes – Grade Classifications 1st

2:1

2:2

3rd

Fail

Fail - NS

Other

2010-2011

32%

17%

13%

17%

17%

3%

1%

2011-2012

1%

5%

18%

59%

10%

5%

2%

2012-2013

18%

22%

32%

18%

7%

2%

1%

2013-2014

5%

37%

35%

17%

3%

2%

1%

2014-2015

7%

33%

41%

15%

2%

1%

1%

2015-2016

20%

20%

37%

16%

1%

2%

4%

2016-2017

25%

27%

42%

3%

0%

0%

3%

2017-2018

34%

49%

17%%

0%

0%

0%

0%

Outcomes – Student Confidence Confidence Levels 2010 Pre-Survey Uncertain to very anxious

72%

Post-Survey Uncertain to very anxious

28.9%

2011

2012

2013

2014

2015

2016

76.7% 72.1% 63.1% 58.6% 67.6% 62.2%

52%

30.9% 24.4% 32.6%

--

37.7%

Student Feedback

experience was great because it “ The allowed students to have instant feedback in a relaxed environment’

“

I don’t think that the whole module should be 100% groupwork as it puts too much stress on certain group members when others do not pull their weight’

feel it should be optional to “ Iwork in a group as I have found

it very difficult at times’

“

Having bad people in your group can greatly effect your grade which is unfair’

felt more connected to the marking “ Iprocess and felt very comfortable to discuss grades and improvements with you, the marker’

the set up of the marking process “ Iandenjoyed would enjoy having that as an option again!’

Staff Feedback

“

Beforehand, I was slightly apprehensive about the whole idea of having to ‘perform’ in front of the students and being put in the spot to come up with a mark that I then needed to justify ‘live’ to them.

“

However, it turned out to be a very enjoyable situation which was no different from the usual marking process, but with the added bonus that it was done right there and was over and done in situ, plus I was sure that at least this one time, the students were actually engaging and digesting my feedback and they seemed both receptive and mostly happy with the outcomes’

Performance issues:

Immediacy of feedback:

Staff Feedback

“

My only comment would be about managing student expectations before the process starts. The reason why I say this is because some groups displayed a clear tendency at under-evaluating themselves, which I suspect it is related to a lack of familiarity with the process and also a possible shyness / fear of challenging the ‘authority’ of the lecturers’

“

On the other hand, the two groups (I think) that over-evaluated their performance, both needed some extra discussion / explanation about why their performance wasn’t as good as they thought it was, and I remember that at least one of them didn’t took well to the feedback process and seem to have a ‘we know better’ attitude’

Power structures:

Guidance and managing expectations:

Further reflections:  Peer Assessment  The challenge of encouraging partnership working

amongst the students themselves  Anonymous marking – fairness of marks given/group

dynamics  Response: open peer assessment at each group

meeting (based on group distribution of credits)

Further reflections:  Partnership working around a live project has generated a

sense of collective ownership and confidence amongst the students  Emphasis on delivery style to engage students and to help

contextualise statistical approaches  Management of expectations – notably around final grade  Anxiety stems from a lack of awareness of what statistics

involves  Over-estimate student numeracy levels on entry and there

is a clear need to review transition support

References BAHARUN, N. AND PORTER, A. (2009) Teaching statistics using a blended approach: Integrating technologybased resources, Working Paper Series Faculty of Engineering and Information Science, Centre for Statistical & Survey Methodology, University of Wollongong.

COTTEE, M., RELPH, A. AND ROBINS, K. (2014), Skills in Mathematics and Statistics in Business and Management and Tackling Transition, HEA, York.

CRUISE, R., CASH, R. AND BOLTON, D. (1985) Development and validation of an instrument to measure statistical anxiety. Paper presented at the annual meeting of the American Statistical Association Statistics Education Section. Las Vegas, NV. DAWSON, P. (2014) Skills in Mathematics and Statistics in Economics and Tackling Transition, HEA, York.

HODGEN, J., McALINDEN, M. AND TOMEI, A. (2014) Mathematical Transitions - A Report on the Mathematical and Statistical Needs of Students Undertaking Undergraduate Studies in Various Disciplines, HEA, York.

HULME, J.A. AND DE WILDE, J. (2014) Tackling Transition in STEM Disciplines - Supporting the Science, Technology, Engineering and Mathematics (STEM) student journey into higher education in England and Wales, HEA York.

ONWUEGBUZIE, A. J., DAROS, D. AND RYAN, J. M. (1997) The components of statistics anxiety: a phenomenological study. Focus on Learning Problems in Mathematics, 19, 11–35.

PERNEY, J. AND RAVID, R. (1991) The Relationship Between Attitudes Towards Statistics, Math Self-Concept, Test Anxiety and Graduate Students' Achievement in an Introductory Statistics Course, unpublished manuscript, National College of Education, Evanston, IL. SCOTT-JONES, J. AND GOLDRING, J. (2014) Skills in Mathematics and Statistics in Sociology and Tackling Transition, HEA, York.

Students as Partners in Research and Assessment An Applied Reflection from a Level 5 Research Skills Module Dr Andrew Clegg Principal Lecturer Learning and Teaching Programme Co-ordinator for Tourism Management