This document provides an overview of data-driven instructional management (DDIM) in educational institutions. It discusses collecting data from various sources like tests, observations, and assessments. This data is then analyzed using different techniques to inform instructional decisions and improvements. The goals of DDIM are to use data and evidence to guide teaching and learning at the school, district, and national levels. The document outlines the process of data collection, analysis, benchmarking, and taking action to forecast achievement based on the data.

1. Management Strategies in
Educational Institutions

2. Course Code: 8615
Unit 8
Muhammad Inam Waris
PhD (Education) Scholar
0333-6263255
warisinaam@gmail.com
DATA DRIVEN INSTRUCTIONAL
MANAGEMENT

3. WELCOME TO AIOU’S VIRTUAL
CLASSROOM SYSTEM
Instructions for students:
 Please mute your microphone while class.
 Don’t engage in chatting with other students
 Ask questions if any using public chat feature
 Please note that all activities are being
recorded

4. After studying this unit, you will be able to:
 1. Describe and explain the basic concept and theory behind
DDIM
 2. Set goals for data collection, analysis and decision making
 3. Apply various assessment techniques to generate useful data
about learners
 4. Analyze the data for future improvements in curriculum and
instruction
 5. Develop action plans for individual, group and classroom
instruction in the light of evidence
UNIT 8: DATA DRIVEN
INSTRUCTIONAL MANAGEMENT

5.  Instructional management is a process of decision
making process, which helps to execute the
teaching and learning as well as to create an
effective learning environment.
 So that much the goals of education are achieved.
INSTRUCTIONAL MANAGEMENT

6.  Data-driven instruction is an educational approach that
relies on information to inform teaching and learning.
 The larger goal of DDIM is to provide the information
regarding learning and instructional practices for informed
decision making at school, district, province and national
level.
 Collecting good, reliable data takes discipline.
 Properly collecting data requires a level of discipline that
most people aren’t inherently comfortable with.
DATA DRIVEN INSTRUCTION

8.  The action of assessing someone or
something.
 Assessment in its traditional meaning is to
collect data for the purpose of evaluation.

9. SOURCE OF DATA
 Teacher made tests and activity sheets.
 Observation sheets of Classroom Participation
 Home Observation Sheets For Parents
 Homework Assessment Rubrics
 Online profiles and Analytics
 Final Examination and Evaluation

18. Input
Process
Output

20. FORMATIVE AND SUMMATIVE
ASSESSMENT DATA

24. • In Data driven Instructional Management procedures, data
analysis goes parallel with data collection and
assessments.
• As a result of any formative assessment process, a teacher
may analyze the information and immediately adjust a
current lesson, or may decide to refine the next lesson, or
decide to plan different experiences for different
ANALYSIS

25. • Organization of data the based on consistency,
uniqueness and logic.
• Exploratory Data Analysis (EDA) (discovery of new
features)
• Confirmatory Data Analysis (CDA) (proof of
hypotheses)
• Qualitative Data Analysis (QDA) (conclusions drawn)
Steps & Stages for Analysis Process

29. THREE TYPES OF BENCHMARK
 Vertical scheme: Within one subject area to
measure consistency between different grade
levels.
 Horizontal Scheme: Applied to ensure
consistency between all members of a certain
classroom taking a given subject.
 Common benchmark evaluations: administered
to all students in the same grade level and course.

30. ACTIONS
 We need to take actions then after whole procedure
i.e. started from data collection and finished on
benchmarking.
 In DDIM multiple data sources guide the teachers
and management at all levels. School level data
describes position of each classroom over all and it
is mainly a source of building teachers profile; while
class level data provides information regarding each
student across various subject areas.

31. QUESTIONS

33. ASSIGNMENT
FORECASTING ACHIEVEMENT
MODELS
WhatsApp me
0333-6263255