AERO Workshop: Constructing and Using OUAC and OCAS Datasets

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AERO Workshop: AERO Workshop: Constructing and Using OUAC Constructing and Using OUAC and OCAS Datasets and OCAS Datasets Presentation to HEQCO - June 19, 2009 Dr. Robert S. Brown Dr. Robert S. Brown Organizational Organizational Development/ Development/ Research and Information Research and Information Services Services Toronto District School Toronto District School Board Board

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AERO Workshop: Constructing and Using OUAC and OCAS Datasets. Dr. Robert S. Brown Organizational Development/ Research and Information Services Toronto District School Board. Presentation to HEQCO - June 19, 2009. Part 1: OUAC Datasets. Open the OUAC e-mail you will receive from AERO - PowerPoint PPT Presentation

Transcript of AERO Workshop: Constructing and Using OUAC and OCAS Datasets

Page 1: AERO Workshop: Constructing and Using OUAC  and OCAS Datasets

AERO Workshop:AERO Workshop:

Constructing and Using OUAC Constructing and Using OUAC

and OCAS Datasetsand OCAS Datasets

Presentation to HEQCO - June 19, 2009

Dr. Robert S. BrownDr. Robert S. BrownOrganizational Development/Organizational Development/

Research and Information ServicesResearch and Information Services

Toronto District School Board Toronto District School Board

Page 2: AERO Workshop: Constructing and Using OUAC  and OCAS Datasets

Part 1: OUAC DatasetsPart 1: OUAC Datasets

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a) Open the OUAC e-mail you will receive from AERO

b) Create folder ‘postsec08’ in your ‘C’ hard drive.

c) Save the files in the OUAC e-mail to the folder

‘postsec08’.

d) Open SPSS. Then open all the SPSS syntax files

in the ‘postsec08’ folder.

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e) Run the file ‘read ouac file.sps’

This will read the text file

BEXT_66052_2008.txt

Which has a selection of OUAC

application and confirmation records

Note: Your file for 2008 should be the same,

except that ‘66052’ would be

replaced with your Board ID number.

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GET DATA /TYPE=TXT /FILE='C:\postsec08\BEXT_66052_2008.txt' /FIXCASE=1 /ARRANGEMENT=FIXED /FIRSTCASE=1 /IMPORTCASE=ALL /VARIABLES= /1 REFYR 0-3 F4.0 REFNO 4-9 F6.0 SCHOOL 10-15 F6.0 SSSN 16-27 F12.0 OEN 28-36 F9.0 SURNAM 37-66 A30 GIVENM 67-96 A30 SEX 97-97 F1.0 BIRTHD 98-105 F8.0 CNFCHS 106-107 F2.0 CNFPGM 108-110 A3 CNFUNI 111-112 F2.0 CNFPGG 113-114 F2.0 FILLER 115-126 F12.0 ACTCHS 127-128 F2.0 PGM1 129-131 A3 UNIVD1 132-133 F2.0 PGMCD1 134-135 F2.0 YR1 136-136 F1.0 ENR1 137-137 A1 PFT1 138-138 F1.0 FILLER2 139-140 F2.0

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f) You should now have an SPSS dataset

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Advantage of this dataset: can provide

limited analysis based on school, gender,

age of student.

Disadvantage: student did not necessarily

attend the board and school in the 2007-8

school year.

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CROSSTABS /TABLES= CNFCHS CNFPGG BY sex /FORMAT= AVALUE TABLES /CELLS= COUNT ROW . execute.

FREQUENCIES VARIABLES=CNFUNI /FORMAT=DFREQ /ORDER=ANALYSIS. execute.

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100.0%50.2%49.8%% within Confirmed- choice Number

636319317Count4

100.0%50.0%50.0%% within Confirmed- choice Number

1175587588Count3

100.0%52.6%47.4%% within Confirmed- choice Number

20751092983Count2

100.0%55.0%45.0%% within Confirmed- choice Number

489226892203Count1

100.0%50.3%49.7%% within Confirmed- choice Number

336116891672Count0Confirmed- choice Number

FemaleMaleTotal

Gender

Confirmed- choice Number * Gender Crosstabulation

100.0%50.2%49.8%% within Confirmed- choice Number

636319317Count4

100.0%50.0%50.0%% within Confirmed- choice Number

1175587588Count3

100.0%52.6%47.4%% within Confirmed- choice Number

20751092983Count2

100.0%55.0%45.0%% within Confirmed- choice Number

489226892203Count1

100.0%50.3%49.7%% within Confirmed- choice Number

336116891672Count0Confirmed- choice Number

FemaleMaleTotal

Gender

Confirmed- choice Number * Gender Crosstabulation

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TDSB University Confirmation in 2008: Major Subject Areas by Gender

18%

63%

45%

54%

82%

55%

46%

37%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Arts, Humanities &Social Sciences

Engineering/AppliedSciences

Commerce/Business Science

Pro

po

rtio

n o

f stu

den

ts

Female Male

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Confirmed- university

Frequency Percent Valid Percent Cumulative Percent

Valid Toronto 2673 20.8 28.2 28.2

York 1765 13.7 18.6 46.8

Ryerson 1277 9.9 13.5 60.2

Waterloo 872 6.8 9.2 69.4

McMaster 532 4.1 5.6 75.0

Guelph 470 3.7 5.0 79.9

Western 406 3.2 4.3 84.2

Queens 373 2.9 3.9 88.1

Wilfrid Laurier 274 2.1 2.9 91.0

OIT 181 1.4 1.9 92.9

Carleton 122 .9 1.3 94.2

Brock 116 .9 1.2 95.4

Ontario College of Art and Design 111 .9 1.2 96.6

Trent 95 .7 1.0 97.6

Windsor 85 .7 .9 98.5

Ottawa 82 .6 .9 99.4

Laurentian 23 .2 .2 99.6

Lakehead 19 .1 .2 99.8

Nipissing 17 .1 .2 100.0

Total 9493 73.9 100.0

Missing System 3361 26.1

Total 12854 100.0

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Presentation to HEQCO - June 19, 2009

Dr. Robert S. BrownDr. Robert S. BrownOrganizational Development/Organizational Development/

Research and Information ServicesResearch and Information Services

Toronto District School Board Toronto District School Board

Thank you

R08(Post-SecReport\Post-Secondary PPTs\PPT OUAC Dataset19June09) ig.3457)

AERO Workshop:AERO Workshop:

Constructing and Using OUAC Constructing and Using OUAC

and OCAS Datasetsand OCAS Datasets