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Data Recording Quantitative Research

Data Recording Quantitative Research

Introduction

This research focuses on how these platforms influence academic achievement, student engagement, and satisfaction. Participant data, including study hours, grades, engagement levels, and technology access, will be systematically recorded and analyzed to provide insights into the effectiveness of online learning tools in higher education.

Study Information

Field

Details

Study Title:

Impact of Online Learning Platforms on Student Academic Performance

Researcher’s Name:

Dr. Jane Smith

Date of Data Collection:

August 9, 2050

Research Objectives:

To analyze how online learning platforms affect students' academic performance, engagement, and overall satisfaction.

Participant Information

  1. Participant ID: 001

  2. Demographic Details:

    • Age: 20

    • Gender: Female

    • Major: Computer Science

    • Year of Study: Sophomore

Data Variables

Variable Name

Definition

Measurement Unit

Study Hours

Total number of hours dedicated to online learning per week

Hours

Grades

Average percentage score for the last semester

Percentage

Engagement Level

Self-reported engagement with online learning materials, rated from 1 (Very Low) to 5 (Very High)

Scale 1-5

Technology Access

Availability of reliable technology and internet access (Yes/No)

Binary (Yes/No)

Measurement Units:

  • Study Hours: Hours (e.g., 12 hours)

  • Grades: Percentage (e.g., 88%)

  • Engagement Level: Scale 1-5 (e.g., 4)

  • Technology Access: Binary (Yes/No) (e.g., Yes)

Data Collection

  1. Data Entry Fields:

    • Participant ID: 001

    • Study Hours: 12

    • Grades: 88

    • Engagement Level: 4

    • Technology Access: Yes

  2. Predefined Response Options:

    Engagement Level:

VeryLevel

Description

1

Very Low

2

Low

3

Moderate

4

High

5

Ver High

  • Technology Access:

  • Yes

  • No

  • Space for Observations:

    Notes: The participant demonstrates high engagement in online learning and reports consistent access to technology. This has contributed to a strong academic performance with a high average grade. The participant’s engagement level suggests effective use of online resources.

Data Validation

  1. Error Checking Mechanisms:

    • Ensure Study Hours and Grades are entered as positive integers.

    • Validate that Engagement Level is within the 1-5 scale and Technology Access is recorded accurately as Yes or No.

    • Cross-check for any discrepancies in Grades and Study Hours to ensure consistency.

  2. Missing Data Flags:

    • All required fields are completed. Flag entries where Participant ID, Study Hours, or Grades are missing or incorrectly entered for follow-up.

Analysis Preparation

  1. Coding Instructions:

    • Study Hours: No coding required; use raw numeric values.

    • Grades: No coding required; use raw percentage values.

    • Engagement Level: Convert scale 1-5 to numerical values for statistical analysis.

    • Technology Access: Convert Yes/No responses to binary values (1 for Yes, 0 for No).

  2. Data Summary:

    • Mean Study Hours: 12 hours

    • Median Study Hours: 12 hours

    • Standard Deviation Study Hours: 0 hours (indicating no variance)

    • Mean Grades: 88%

    • Median Grades: 88%

    • Standard Deviation Grades: 0% (indicating no variance)

    • Engagement Level Distribution: Predominantly high engagement, with an average rating of 4.

    • Technology Access Analysis: All participants report having reliable technology access, indicating a uniform condition that supports the online learning environment.

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