Fundermentals Of Data Processing
- Education
- 200 level
- 2 credit units
- 157 pages
- 16 units
This course is designed to equip students with knowledge of data processing in technical and vocational education, especially Business Education research. You will learn the components of data processing, hardware and software components, file management and organization in Business Education-based data. It will also interest you to learn about basics of research, approaches and designs with data gathering techniques. Relevant statistical tools you can use to analyse your data would be across and how to write your research reports.
About this course
- Difficulty
- Intermediate
- Study hours
- 200 hours
- Maths
- Intermediate
- Content
- Theoretical, practical, case study, problem solving, research
- Practical work
- Yes
- Assignments
- Tutor marked assessments
- Final examination
What you'll read
The real module and unit structure of BED212, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
BED212 · UNIT 1: CONCEPTS OF DATA PROCESSSING
Think about any collected data that you have experience of; for example, weight, sex, ethnicity, job grade, and consider their different attributes. These variables can be described as categorical or quantitative.
What you should be able to do
- Gain in-depth knowledge of data processing
- Appreciate the historical perspective of data processing
- Acquire skills in generating researchable problems
- Understanding of the basic research designs
- Appreciate various research data collection tools
- Demonstrate skills in utilizing appropriate statistical tools
- Write comprehensive research reports
What it prepares you for
- Data Analyst
- Business Analyst
- Research Assistant
- Statistician
- Database Administrator
- Education
- Business
- Research
- Government
- Technology
- SPSS
- Microsoft Excel
- SAS
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 3: STATISTICS IN EDUCATIONAL RESEARCH
Unit 5: Testing of Hypothesis
Advanced statistical analysis requires strong mathematical and analytical skills.
- Module 1: INTRODUCTION TO DATA PROCESSING
Unit 1: Concept of Data Processing
Understanding the underlying principles of data processing is essential for effective application in various fields.
A suggested way through it
13 weeks, about 56 hours in total. Yours will differ.
- Week 1Module 1: Introduction to Data Processing
Unit 1: Concept of Data Processing · 4 hours
Define data processing. Explain components of data processing. List functions of data processing. Explain types of data.
- Week 2Module 1: Introduction to Data Processing
Unit 2: Historical Perspectives of Data Processing · 4 hours
Discuss the historical perspective in data processing. List application of data processing. Explain necessary steps for effective data processing.
- Week 3Module 1: Introduction to Data Processing
Unit 3: Hardware Supports in Data Processing · 4 hours
Identify input, processing and output components of data processing. Discuss the anatomy of a computer system. Mention specific examples of output devices. Differentiate between plotters and printers.
- Week 4Module 1: Introduction to Data Processing
Unit 4: Software Elements in Data Processing · 4 hours
Define software. Differentiate between system software and application software. List the functions of operating system. Enumerate the considerations to be made in selecting application software.
- Week 5Module 1: Introduction to Data Processing
Unit 5: Data Processing File Management and Organisation · 4 hours
Describe content of a computer file. List operations that can be performed on the file. Differentiate between relative and indexed files. Discuss different data capturing techniques.
- Week 6MODULE 2: DATA PROCESSING IN EDUCATIONAL RESEARCH
Unit 1: Research Problem: Identification and Formulation · 4 hours
Define the term research problem. Mention roles of theory in research formulation. List sources of research problem. Explain both internal and external criteria for research problem formulation. Describe considerations in selecting a research problem. Discuss characteristics of a good research problem.
- Week 7MODULE 2: DATA PROCESSING IN EDUCATIONAL RESEARCH
Unit 2: Research Questions and Hypotheses for Data Processing · 4 hours
Define a research question. Explain PICO approach to research question. Explain the characteristics of research questions. Describe hypotheses with specific example.
- Week 8MODULE 2: DATA PROCESSING IN EDUCATIONAL RESEARCH
Unit 3: Research Approaches and Designs I · 4 hours
Differentiate between quantitative and qualitative research approaches. Explain the principles of quantitative research. Discuss the process of qualitative research.
- Week 9MODULE 2: DATA PROCESSING IN EDUCATIONAL RESEARCH
Unit 4: Research Approaches and Designs II · 4 hours
Explain descriptive survey design. Enumerate areas of strengths and weaknesses of experimental research design. Identify possible insights to goals which exploratory research that are intended to produce. Describe longitudinal research design.
- Week 10MODULE 2: DATA PROCESSING IN EDUCATIONAL RESEARCH
Unit 5: Data Collection Tools and Methods · 4 hours
List research instruments and explain types of questionnaire. Differentiate between focus group and tasting panel. Enumerate limitations of interviews as research tool.
- Week 11MODULE 3: STATISTICS IN EDUCATIONAL RESEARCH
Unit 1: Introduction to Statistics · 4 hours
Define statistics. Explain types of statistics. Organize a set of scores. Explain graphical representations.
- Week 12MODULE 3: STATISTICS IN EDUCATIONAL RESEARCH
Unit 2: Methods of Representing Data and Measures of Central Tendency · 4 hours
Construct a pie chart using given data. Construct and describe histogram. Draw a composite table and construct a frequency polygon. Draw a composite table and construct an ogive. Calculate the mean, median and mode of a given data.
- Week 13MODULE 3: STATISTICS IN EDUCATIONAL RESEARCH
Unit 3: Measures of Variability or Spread · 4 hours
Find the range in a given set of scores. Explain and find the quartiles in a distribution. Find the percentiles in a given set of scores. Calculate the variance in a given set of scores. Calculate the standard deviation in a distribution.
Unit 4: Measures of Association/Correlation · 4 hours
Define correlation. Illustrate the scatter-grams of various correlations. Calculate the Pearson r. Calculate the Spearman rho.
Preparing for the exam
- Create concept maps linking data processing components (Units 1-5)
- Practice formulating research questions and hypotheses (Module 2)
- Review statistical formulas and practice calculations (Module 3)
- Focus on understanding research designs and data collection methods (Units 3-5, Module 2)
- Study examples of research reports and practice writing summaries (Unit 6, Module 3)
Questions students ask about this course
What is BED212 about?
This course is designed to equip students with knowledge of data processing in technical and vocational education, especially Business Education research. You will learn the components of data processing, hardware and software components, file management and organization in Business Education-based data. It will also interest you to learn about basics of research, approaches and designs with data gathering techniques. Relevant statistical tools you can use to analyse your data would be across and how to write your research reports.
How many units does BED212 have?
BED212, Fundermentals Of Data Processing, has 16 units across 3 modules, over 157 pages of course material. You can read it one unit at a time.
How many credit units is BED212?
BED212 carries 2 credit units, at 200 level in Education.
Is BED212 hard?
BED212 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, practical, case study, problem solving and research work, and it has a practical component.
How long does BED212 take to study?
About 200 hours of study, spread across its 16 units.
How is BED212 assessed?
BED212 is assessed by assignments, tutor marked assessments and final examination.
What can I do with BED212?
Data Analyst, Business Analyst, Research Assistant, Statistician and Database Administrator.