ANIRBAN GHOSH

ASHISH RANJAN

AYAN DAS

MADHUMITA GHOSH

SOMDEEP SEN

ACADEMIC PERFORMANCE PREDICTION THROUGH MULTIPLE REGRESSION

INTRODUCTION

The Data set contains:

Performance of 400 elementary schools from the California Department of Education

Factors like class-size, parent education, student performance, etc.

Objectives:

To find the factors having major influence on the academic performance

To predict academic performance of an school using those factors

FACTORS & THEIR INFLUENCE

Note: Factors have been chosen based on statistical significance

Detailed SAS Code: http://bit.ly/1c08pGE

Factors Impact

English language learners(ELL) Negative

Percentage first year in school (Mobility) Negative

Parent grad school (grad_sch) Positive

Percentage full credential (Full) Positive

Average Class size 4-6 (ACS_46) Positive

INFERENCE & RECOMMENDATION

ENGLISH LANGUAGE LEARNERS

ELLs are one of the fastest growing populations in the public schools

Number of ELLs in CA is healthy due to the geographic location & economic significance

ELL students come from different backgrounds &face multiple challenges

But, the main challenge continues to be the problem in communication

Recommendations:

Provide special coaching to ELLs to ensure that they master English

Special coaching should be done before they get tested in English in core content areas

Ensure that all ELL students receive the full range of services

Improve teacher training opportunities so teachers can understand the needs of ELLs

PERCENTAGE FIRST YEAR IN SCHOOL

Students making non-promotional school changes is known as mobility

California students, like students in the rest of the U.S., are highly mobile

Mobility happens due to following reasons:

Families changing residences

School changes initiated by students especially in California

School changes initiated by schools especially in California

PERCENTAGE FIRST YEAR IN SCHOOL(CONTD.)Recommendations:

Families should:

Attempt to resolve problems at school before initiating transfer

Make changes between semesters or at the end of the school year

Schools should:

Counsel students to remain in the school if at all possible

Prepare in advance for incoming transfers

Assess the past enrollment history of incoming students

Assess the number of previous school changes

Facilitate the transition of new students as soon as they arrive

PARENT GRAD SCHOOL

Research shows US students spend less than 15% of their time in school

Therefore parent involvement is as important as the time spend in school

Checking homework, attending school meetings, influences student performance

Educated parents finds it easier to get involved than the others

Recommendations:

Look to ensure that parents with school graduation lie between 65-70%

Conduct parent interview during the admission of the students

Also take initiatives to increase parent engagements

But schools shouldn’t limit a parent’s involvement based on socio-economic status

PERCENTAGE FULL CREDENTIAL Experienced teachers are more effective at raising student

Experienced teachers are also more likely to be fully credentialed also

Hence teacher retention could be instrumental in performance improvement

Shortage of fully credential teachers is a prime reason for low performance & mobility

Many assume that financial incentive is the silver bullet; but that is only partially true

Recommendations:

Financial incentives can make schools more attractive to more qualified teachers

Money is Necessary, But Clearly Not Sufficient

Teachers often leave due to poor working conditions, and lack of administrative support

Schools should recruit & develop administrators who can draw on the expertise of teachers

AVERAGE CLASS SIZE 4-6

Improvement in avg. class size in 4-6 grade((ACS_46) tends to improve performance

ACS_46 can be improved when:

Mobility is low

Promotion of student’s from one grade to another is high

So, it can be said that ACS_46 is an indicator of the overall academic performance

Recommendation:

Focus should be on all the recommendations mentioned previously to improve ACS_46

THANK YOU