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Using personality type to predict student success in a technology-rich classroom environment : 

Using personality type to predict student success in a technology-rich classroom environment Lauren H. Brown, Ed.D. Donna Burton North Carolina State University

Why do this research?: 

Why do this research? Personal Interest Millennial generation Adviser connections Student Success

The Millennials: 

The Millennials Generational Differences Parental ties Digital Generation Prevalence of technology Class Communication Personal life Faculty/student relationships

Personality Theory: 

Personality Theory Why personality theory? Carl Jung Isabel Myers and Katherine Briggs-Myers The dimensions Population differences

Personality Theory in the Classroom: 

Personality Theory in the Classroom Information gathering Teaching vs. Learning- dissonance

Technology in the Classroom: 

Technology in the Classroom Uses Age differences Instructor preference Congruence with students’ learning North Carolina State University

Personality Theory and Technology in the Classroom: 

Personality Theory and Technology in the Classroom Instructor use Student use The internet Lack of research

The TF and SN Dimensions and Technology: 

The TF and SN Dimensions and Technology Decision making Thinking Feeling Information gathering Sensing Intuiting

The Problem: 

The Problem The new students and advisers/faculty Personality theory and success in the new environment Lack of specific, predictive research

Purpose: 

Purpose To further investigate if a student’s personality type, specifically on the Sensing/Intuiting and Thinking/Feeling scales, can be used to predict success in a technology-rich classroom environment.

Research Questions: 

Research Questions What is the predictive value of an individual’s preference for Sensing vs. Intuiting on achievement in a model that controls for gender differences and SAT score? What is the predictive value of an individual’s preference for Thinking vs. Feeling on achievement in a model that controls for gender differences and SAT score?

Conceptual Framework: 

Conceptual Framework

Methodology: 

Methodology Design Population and Sample The MBTI Validity Reliability Data Collection Data Analysis

Descriptive Statistics: 

Descriptive Statistics

Correlation Statistics: 

Correlation Statistics

Regression Analysis- Model 1: 

Regression Analysis- Model 1

Regression Analysis- Model 2: 

Regression Analysis- Model 2

Uniqueness Indices- Model 1: 

Uniqueness Indices- Model 1

Uniqueness Indices- Model 2: 

Uniqueness Indices- Model 2

Males vs. Females on TF: 

Males vs. Females on TF

Males vs. Females on SN: 

Males vs. Females on SN

T-test Results-Comparing Means: 

T-test Results-Comparing Means

Discussion- Results: 

Discussion- Results S vs. N T vs. F

Discussion- Significance: 

Discussion- Significance NC State classroom improvements Millennials and technology- assumptions Alternative ways to use standard assessments Implications- new tool for advisers Link to past research

Limitations: 

Limitations Chemistry 101 Class difficulty Enrollment Timing Professor grading styles Not completely random selection Course repeat

Suggestions for Future Research: 

Suggestions for Future Research Class comparison Repeat- why? Upper-class students Longitudinal

Summary: 

Summary Questions? Thank you for attending. Please fill out the evaluation form before leaving. Email lauren_brown@ncsu.edu donna_burton@ncsu.edu