This paper demonstrates that when education programs are delivered as if all students have identical learning styles and needs, the students with unique learning styles are put at a disadvantage. On the other handed the authors also describe how the application of digital technology, in particular, the Internet of Things (IoT), is making inclusion possible and democratized education affordable.
This research provides data driven insights that can be used by engineering educators to better understand distinct segments of undergraduate students. Three clusters emerged that delineated students into three distinct typologies: Steadiness Compliance (SC); Influencing Steadiness (IS) and Dominance Influencing (DI) typology. This affirms once again that students are unique and individual differences require different teaching and learning approaches.
This study suggests that for a variety of reasons, male and female students do not bring in the same sets of soft skills into a college classroom. The impact of their educational experiences on male and female students is different.
The U.S. Equal Employment Opportunity Commission (EEOC), drawing their interpretation from the 1964 Civil Rights Act Title VII, states that an employer may not use an employment or hiring practice that, even though neutral on its face and applied to all applicants or employees equally, disproportionately impacts members of protected categories, including divisions by gender, race, disability or veteran status.
The TTI Success Insights 2021 disparate impact study examined behaviors, motivators, Hartman, DNA 23, DNA 25, and Emotional Quotient assessments to determine whether our assessments create any posibility of contributing significant differences with regard to relevant protected classes during an employment or hiring process. This USA only study found that significant contributions related to the tools themselves are unlikely to be introduced.
The 2021 Motivation Insights Reliability Study is an internal consistency reliability study and is part of TTI SI’s ongoing continuous improvement process. This study uses a measurement of reliability called the Cronbach’s α (alpha). Cronbach’s α is a measure of the lower bound estimate of the reliability of a psychometric assessment. Cronbach’s α is a scalar taking values between 0 and 1, inclusive. Generally speaking, the closer the score is to one, the more reliable an assessment may be considered. The scales for the Motivation Insights are labeled Theoretical, Utilitarian, Aesthetic, Social, Individualistic, and Traditional.
