Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 111 - 120 of 399
Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of participation in San Diego—EARN!, a Work Advancement and Support Center (WASC), on participants’ earnings, employment, educational attainment and…Study Type: Descriptive Analysis
The study presented findings from a review of after-school programs in the United States focused on improving science, technology, engineering, and mathematics (STEM) skills and increasing access to…Study Type: Descriptive Analysis
The study examined existing empirical research on the challenges that minority women have faced in science, technology, engineering, and mathematics (STEM) disciplines at the undergraduate and…Study Type: Descriptive Analysis
The study described factors that might increase young Latinas’ enrollment in pre-engineering programs. The authors reviewed a case study of middle and high school Latina students in the rural…Study Type: Descriptive Analysis
The authors described two programs partnering with California community colleges—the Mathematics, Engineering, Science Achievement Community College Program (MCCP) and the CalWomen Tech Program—that…Study Type: Descriptive Analysis
The authors sought to determine whether the complexity of a mother’s occupation (or the quality of employment as defined by its task complexity, autonomy, and authority) affected her 6- to 13-year-…Women in industrial engineering: Stereotypes, persistence, and perspectives (Brawner & Camacho 2012)
Study Type: Descriptive Analysis
This study explored why more women major in industrial engineering in college than other engineering fields. The authors tabulated quantitative data from eight colleges and universities in the…Study Type: Descriptive Analysis
This study aimed to determine if student characteristics; financial aid receipt; and labor market conditions (such as unemployment, weekly wages, and professors’ salary) predicted doctoral degree…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of providing low-income families with private market housing vouchers on employment, earnings, receipt of public assistance, and receipt of education…Early college, early success: Early college high school initiative impact study (Berger et al. 2013)
Study Type: Causal Impact Analysis
The study’s objective was to examine the effect of Early Colleges, which exposed high school students to college classes, on students’ high school achievement, persistence, and graduation; college…
CLEAR Icon Key
Below is a key for icons used to indicate important details about a study, such as its type, evidence rating, and outcome findings.
High Causal Evidence
Strong evidence the effects are caused by the examined intervention.
Moderate Causal Evidence
Evidence that the effects are caused to some degree by the examined intervention.
Low Causal Evidence
Little evidence that the effects are caused by the examined intervention.
Causal Impact Analysis
Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
Descriptive Analysis
Describes a program, policy, or intervention using qualitative or quantitative methods.
Implementation Analysis
Examines the implementation of a program, policy, or intervention.
Favorable
The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
Mixed
The study found some favorable and some unfavorable impacts in the outcome domain.
None
The study found no statistically significant impacts in the outcome domain.
Unfavorable
The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
Not applicable
Not applicable because no outcomes were examined in the outcome domain.
Favorable - low evidence
The study found at least one favorable impact in the outcome domain, and no unfavorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Mixed - low evidence
The study found some favorable and some unfavorable impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
None - low evidence
The study found no statistically significant impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Unfavorable - low evidence
The study found at least one unfavorable impact in the outcome domain, and no favorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.