While convergent validity tells us our measures are reliable, discriminant validity is what actually holds the model together. Without it, the line between concepts like ...
While convergent validity tells us our measures are reliable, discriminant validity is what actually holds the model together. Without it, the line between concepts like 'Motivation' and 'Engagement' gets blurred, making any further analysis feel a bit hollow. In GenAI research, it’s vital to ensure that 'Utility' and 'Ease of Use' stand on their own statistically; otherwise, we lose the nuance needed to truly explain why students choose these tools.