audit of mathematics learning support in ireland in 2015 - the key...

Audit of mathematics learning support in Ireland in2015 − the key findings

Maura Clancy27th May 2016

Maura Clancy Limerick Institute of Technology 10th Annual Irish Workshop 1 / 36

Colleagues

Dr Anthony CroninDr Cormac Breen

Dr Diarmuid O’SéDr Jonathan Cole


Background The project

MLS beginnings

B First UK initiative - 1990sB On the island of Ireland:

◦ First MLS initiative - 1998 (Northern Ireland)◦ First institute of technology to provide MLS - 1999◦ First Mathematics Learning Support Centre (MLSC) - 2001◦ The Irish Mathematics Learning Support Network (IMLSN) - 2009



Reason for commission

• IMLSN aims:B Act as an informative community of practiceB Provide training and support to members through the sharing of

ideas and best practiceB Provide a mechanism for the provision of opportunities for

collaborative research and development in the area of MLS

You can’t be a big dreamer if you don’t know where you aregoing. You can’t know where you are going unless you firstknow where you are.

Israelmore Ayivor



The survey

• In 2008 Gill et al [1] conducted a complete audit of the number andtype of MLS in the Republic of Ireland• The IMLSN felt a comprehensive up-to-date picture of MLS wasrequired• A special interest group (SIG) was formed in November 2014 to carryout this task• An online survey, consisting of 55 questions, was conducted in April2015• The survey was divided into six categories:

1. Availability and practical operation of MLS2. Staffing and tutors3. Types of support available4. Users of the service5. Reporting and evaluation of MLS activities6. Challenges and developments



Methodology

• A pilot survey was conducted• Relevant contacts were identified at 32 higher level institutions (HEIs)• These were then contacted by email and asked to complete thesurvey• Reassurances of anonymity were given• Respondents were encouraged to complete the survey in two sitting• Follow-up calls, where needed, were made to encourageparticipation



The survey

The survey was completed by 31 HEIs

32%

39%

13%

16%

Uni

IoT

FHE

CELA

Figure 5: Classification of institutions that responded to the survey


The results Level and type of support

Development timeline

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016Year

Uni

IoT

FHE

CELA

Figure 6: Timeline showing when MLS was first established in the institutionssurveyed



Level of support

B 26 HEIs (84%) provide some form of MLSB Lack of funding cited as the main barrier where there is no MLSB 65% of those 26 institutions provide MLS through a MLSC

72%

24%

4%

allstudents

studentsstudyingpar3cularmodules

first-yearstudentsonly

Figure 7: Profile of students accessing MLS



Location

0 1 2 3 4 5 6

various

generalbuilding/classroom

engineeringdepartment

mathsdepartment

library

academichub/learningcentre

Numberofins-tu-ons(n=22)

MLSC

noMLSC

Figure 8: Location of MLS provision

• 77% of MLS offerings have a dedicated space• 32% have an exclusive space



Location

0

1

2

3

4

Uni IoT CELA FHE

Num

bero

fins-tu-

ons(n=

23)

stronglyagree

agree

neutral

disagree

stronglydisagree

Figure 9: Our MLSC is appropriately located



Availability

0

1

2

3

4

5

6

7

1-5hours

6-10hours

11-15hours

16-20hours

21-25hours

26-30hours

>30hours

asrequired

Num

bero

fins-tu-

ons(n=

25)

Figure 10: Number of hours per week the MLS provision is open

• 24% available for 5 hours or less• 64% available for 20 hours or less



Availability by institution type

• In universities, MLS service hours range from “a few" to 48 hours perweek with a mean value of 22.1 hours• In institutes of technology, opening times range from three hours to55 hours per week and the mean is 18.8 hours• There was no evidence of support available at weekends in anyinstitution• In 60% of institutions the MLS service is closed during theexamination period



Stability

• Seven (41%) of the 17 institutions having a MLSC described aspermanent

Figure 11: MLSC permanent or subject to review (n=17)



Stability

• Permanent MLSCs are more prevalent in universities

0

1

2

3

4

5

6

Uni IoT FHE

numbe

rofins,tu,

ons

permanent

subjectto(annual)review

other

Figure 12: Status of MLSC by institution type (n=16)



Type of support: in-person support

B 88% of MLS offerings provide some form of drop-in facilityB Two of the centres do not offer drop-in facilitiesB 64% provide special workshops for particular topics/modules

0

20

40

60

80

100

term,me exam,me summer,me

percen

tageofins.tu.

ons

Figure 13: Provision of workshops during the year (n=15)



Type of support: in-person support

0

20

40

60

80

MLSCmanager lecturer/module

coordinator

students studentswithlecturer'sagreement

percen

tageofins.tu.

ons

Figure 14: Those who request/ initiate the workshops



Type of support: online

•52% of MLS providers do not currently offer some form of onlinesupport (n=25)• 69% of those that don’t currently provide online support plan to do soin the future (n=13)

0 1 2 3 4 5 6 7 8

socialmedia

Skypeappointment

commercialso;ware

email/messageboard

revisionnotes

dedicatedVLE

dedicatedwebsite

Numberofins-tu-ons

Figure 15: Forms of online support on offer



Type of support - popular/effective

0

2

4

6

8

10

12

14

16

one-to-one smallgrouptutorials

onlineresources

worksheets workshops

numbe

rofins,tu,

ons

mostpopular

secondmostpopular

thirdmostpopular

Figure 16: Forms of maths support most frequently used by students

• There was a strong belief that one-to-one support was the mosteffective support


The results Users of the service

User profile

B Mean estimated percentage for first year undergraduates was55% (max 100%)

B Mean estimated percentage for second year undergraduates was22% (max 41%)

B Mean estimated percentage for third year undergraduates was10% (max 35%)

B Mean estimated percentage for fourth year undergraduates was4% (max 18%)

B Mean estimated percentage for postgraduates was 3% (max 30%)B MLS pervades almost every discipline with engineering, science

and business (in that order) being the most prelaventB Highlights that MLS tutors need to be capable of dealing with the

maths as applied in a wide range of contexts



User profile

status 0-10% 11-25% 26-50% 51-75% 76-100%traditional 1 1 5 3 5non-traditional 4 5 4 3 0disability 6 2 0 0 1international 5 2 0 0 0

Table 1: Status of MLS users by percentage bands within institutions

• Survey results for student academic stage, subject area and statusprofile highlight the diversity of those requiring MLS in third-leveleducation



Problem topics

26%

25%14%

9%

6%

5%

5%3%

3% 2%2%basicalgebra

calculus

sta5s5cs

arithme5ccalcs

trigonometry

logs

analysis

matrices

linearalgebra

numericalmethods

graphs/func5ons

Figure 17: Topics which cause most difficulty (n=22)



Duration of student visits

0

2

4

6

8

<30minutes 30-59minutes 60+minutes

numbe

rofins,tu,

ons

anecdotal

evidence-based

Figure 18: Average duration of a student visit



Student engagement with MLS

slow/busy times in MLS Number of institutionsslow to start 8busy near mid-term exams / CA 9busy end of semester 7slow end of semester 2busy near exam time 7busy summer / repeat exams 2


The results Staffing and tutors

Staff numbers

20%

40%

16%

16%

8%

1-2

3-5

6-10

11-20

>20

Figure 19: Percentage of institutions having a given number of staff (n=25)



Manager/ coordinator

36%

28%

8%

12%

16% full+me

partoflecturing/admindu+es

partofcontract,separatefromlecturing/admindu+es

voluntary

nomanager

Figure 20: Status of the role of manager/ coordinator of MLS (n=25)



Manager/ coordinator

Uni IoT FHE CELAfull time 3 4 1 1part of lecturing/ admin duties 2 4 0 1part of contract, separate fromlecturing/ admin duties 2 0 0 0voluntary 1 0 1 1no manager 1 3 0 0

Table 2: Nature of managerial role by institution type (n=25)



Staffing sources

0

10

20

30

40

50

60

70

80

full-/mestaff

undergrads postgrads-hourly

postgrads-scholarship

externalstaff

voluntary other

percen

tageofins.tu.

ons

Figure 21: Percentage of institutions procuring staff from various categories(n=25)



Staffing

full-time undergradspostgrads

hourlypostgrads

scholarship external voluntary otherUni 56 67 67 22 44 11 11IoT 82 18 45 0 45 0 0FHE 100 0 0 0 0 0 0CELA 0 100 100 0 0 0 0

Table 3: Percentage of institutions, by institution type, procuring staff fromvarious categories (n=25)



Tutor training

44%

52%

4%

yes

no

noresponse

Figure 22: Training programme for tutors (n=25)

• Since this survey three universities facilitated full-day tutor trainingprogrammes• Based on four workshops developed by an IMLSN special interestgroup on MLS tutor training• Attended by 42 participants from six institutions



Staff issues

B Securing and retaining good tutors is a key issueB When asked how their MLS could be improved, 54% of

respondents referred to tutoring staff in various ways:• more tutors• permanent tutoring staff• tutor training

B In fact, only two (out of 25 respondents) listed "more funding"ahead of "tutors" as the priority for improvement

B Several suggested that tutors be given permanent contracts and abetter salary so as to "encourage the good tutors to stay longerand see it [MLS] as a viable career"

B A recent UK report by Tolley and MacKenzie [2] noted that seniormanagement from several UK HEIs suggested the need forappropriate MLS training, leading to some kind of professionallyaccredited status.


Previous surveys Ireland 2008 and 2015

Characteristic of service 2008 2015MLS offered through a MLSC 38% 65%Permanent MLSC 36% 41%Opening hours ≤ 10 38% 36%Opening hours 10-20 31% 28%Opening hours > 20 31% 36%MLS offered to all students 54% 72%MLS offering drop-in service 62% 88%MLS offering online support 77% 46%MLS funded from various sources within the institution 54% 92%MLS funded from external sources 38% 4%No additional funding 8% 4%Maintain attendance/ usage records 85% 80%MLS staffed by institutional staff 46% 72%MLS staffed by postgraduate students 38% 56%


Previous surveys Ireland 2015, UK 2012 and Australia 2007

Characteristic of service IR 2015 UK 2012 AU 2007Institutions offering MLS 84% 85% 82%MLS offering drop-in service 88% 82% 72%MLS offering workshops 64% 6% 21%MLS offering appointments 44% 8% 38%MLS staffed by postgraduate students 56% 11% N/AStaff have MLS publications 34% 31% N/AMLS based in Maths Dept 32% N/A 44%MLS based centrally 41% N/A 41%MLS funded centrally 54% N/A 59%MLS funded by Maths Dept 17% N/A 38%


Summary Summary

B 84% HEIs on the island of Ireland provide some form of MLSB The nature, scale and range of MLS offerings differ significantly

across the institutions surveyedB 41% of centres are subject to annual reviewB One-to-one is the type of support most favoured by studentsB One-to-one is also viewed by practitioners as the most effective

supportB Many practitioners feel that the profile of MLS needs to be raised

When asked what MLS practitioners most needed from theIMLSN, the following quote epitomises several responses:

Keep raising the profile of MLS and the centres. Keeppressure on institutions and government to recognise theneed to properly support us


Summary Summary

THANK YOU

We would like to extend a sincere thank you to The National Forum forthe Enhancement of Teaching and Learning whose funding supportassisted the completion of this work.


Summary Summary

References

[1] Gill, O., Johnson, P. and O’Donoghue, J. (2008) An audit ofmathematics support provision in Irish third level institutions. CEMTL(Regional Centre for Excellence in Mathematics Teaching andLearning), University of Limerick.

[2] Tolley, H. and Mackenzie, H. (2015) Senior managementperspectives on mathematics and statistics support in highereducation. Sigma, Loughborough University. Accessed viahttp://www.sigma-network.ac.uk/wp-content/uploads/2015/05/sector-needs-analysis-report.pdf

[3] Fitzmaurice, O., Cronin, A., Ni Fhloinn, E., O’ Sullivan, C. andWalsh, R. (2016). Preparing tutors for mathematics learning support.MSOR Connections. Vol.14, No.3


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