given the NILA’s leadership framework and curriculum focus onthe development in these areas. The average mean for leadership self-efficacy increased from 4.0to 4.3. The increase was significant, and it shows that NILA had a measurable positive effect.Nevertheless, the effect may or may not be sustainable. Most of the change was explained by thelower values (pre-test minimum=2.6, post-test minimum=3.0), which is reflected in a smallerstandard deviation for the post-survey. This shows that the effect may be larger for those whocome in with lower self-efficacy than those who are already confident in their abilities. While thesample size was small, the EFA analysis is statistically significant to tentatively support ourhypothesis. However, this can
, unlike the other measures, there was much more room forgrowth. However, there was no significant change detected. Thus, we cannot conclude that thelab kit and curriculum relate to self-beliefs.Table 4. Self-Efficacy results (N = 39) Initial Change Mean: 3.17 Change Mean = 0.17 Standard Deviation: 1.16 Change Standard Deviation =1.40 Conclusion and Future Directions Overall, the lab kit and neuroscience curriculum were most successful in the area ofimproving science aspirations for diverse students. Additional changes need to be made in futureiterations to the curricular materials
captured by SHPE’s long-term NRP throughout the year.While several internal components of McCormick’s model have been validated, NILA’scurriculum serves as a unique opportunity to measure self-efficacy, a challenging aspect tomeasure [47-50], and validate in the context of Hispanic STEM professionals.Figure 2. McCormick’s Social Cognitive Model of Leadership [38], reproduced with permission from the publisher.3. SHPE’s Leadership and Chapter Programming Mapping to McCormick’s Model3.1 NILA’s Curriculum Mapped to Leader Cognitions Figure 3 shows the concept mapping of NILA’s 2019 curriculum to the leader cognitionportion of McCormick’s model [48]. Following the OGSM model presented in Section 2.1,NILA’s objective is captured by McCormick’s
constructs in the population. The constructs are all positively correlated, withmagnitude of correlation corresponding to the size of the bubble. This is shown by the checkedbubbles intersecting any two pairs of measures in Figure 2. It is evident that Anticipatory Cognitionis correlated and significant to several of the measures, but lacks significance against stereotypethreat, isolation, extant knowledge and future anticipation. For example, the weaker theparticipants infer the stereotype threat, the higher is their attention and focus to solving theirresearch problem. It is also evident from this Figure that Academic Self Efficacy is predominantlycorrelated
specified). In addition, we assessed social cognitive variables related to educationaland career decision making, including engineering self-efficacy, expectations for the field ofengineering, commitment to major and degree completion. In 2019, students were asked if theyidentified as a member of the LGBTQ+ community, allowing for a better understanding of thesestudents’ experiences. Data from all three survey years were combined to investigate trends oncritical measures related to persistence in engineering. We found that students’ assessment of theeducational environment (professors and student interactions) were relatively stable, while otheraspects of the environment (experiences of stereotyping and harassment) significantly increasedacross the
Social & Emotional SkillsPhysical Space • Layout • Confidence • Collaboration • Self efficacy • Open • Innovation • Sense of • Safe • Creativity belonging • Accessible • Partnerships The bad news… Women and minoritized students are underrepresented Tension
-efficacy theory is developed in the field of behavioral change and hestates that “…cognitive processes mediate change but that cognitive events are induced and alteredmost readily by experience of mastery arising from effective performance” [18]. The mastery thatarises from this effective performance is defined as confidence. Confidence is the self-belief inpeople’s competence or chance to successfully complete a task [19]. Perceived self-efficacy instudents is defined as the students’ beliefs in themselves to regulate their own learning, level ofmotivation, and master academic activities, which lead to academic accomplishments [20]. Self-efficacy theory is used in this study to help students develop STEM-confidence. Student views of
in sense of belonging were also reported between domestic and international STEMdoctoral students [10],[13], in turn underscoring the need for increased understanding sense ofbelonging from the international student perspective, particularly in the context of engineeringdoctoral education.Our earlier work [1] related to understanding international doctoral students’ sense of belongingis a first step in responding to this identified need. We investigated students’ perception of theirinterpersonal interactions with peers and faculty and the associated relationships on their sense ofbelonging. The findings include a conceptual model that demonstrates the different constructs ofbelongingness, (e.g., engineering self-efficacy, academic sense of
literature has identified a wide range of factors that determine whether a community will be resilient. These include (with examples relative to this work), infrastructure (computing and internet), financial (wealth and employment), human and cultural (academic family expectation, food security), social (support networks), political (college governance), and the mental outlook of individuals (Patel, et al, 2017, NASEM, 2019). Resilience has been studied at scales ranging from individuals to broader communities, which highlights both internal and external supporting factors. Internal factors reside inside an individual agent and may be characterized by such psychological traits and skills as optimism, creativity, spirituality, humor, self-efficacy
HBCU, met and exceededthe diversity of most REU programs across the nation. In terms of broadening participation inengineering, note that the majority of the participants were African-American, while a significantnumber were non-African American. The last cohort showed more gender and ethnic diversity,with ethnic diversity reflecting just as many African-American participants as non-AfricanAmerican participants; gender percentages were also equal by the final year of the program.evaluation methodologyThe evaluation plan included a hypothesis of increased modeling self-efficacy from pre-test topost-test. Yildirim et al. [4] developed an Engineering Modeling Self-Efficacy (EMSE) instrumentwith 36 items and 7 dimensions drawn from Tsang’s (1991
, components that the majority of engineeringdepartments are adopting include rapid prototyping tools, such as additive manufacturingmachines (3D printers) and laser cutters [3], [4].Makerspaces and Engineering Education. Makerspaces have become popular withinengineering education. Integrating a makerspace into an engineering curriculum can be adaunting task given the scope and sequence of university engineering coursework. Recentresearch found that over a three-month period, students who took part in a course that integrateda class project within the makerspace were positively and significantly impacted in the domainsof technology self-efficacy, innovation orientation, affect towards design, design self-efficacy,and belonging to the makerspace [5
tutoring spaces often reflect the demographics of the department oruniversity at large. Tutors also bring their own identities and biases into these spacesthat can serve to enhance or diminish the self-efficacy and sense of belonging ofattendees. If these factors are not explicitly addressed by training or intentionalhiring, administrators should almost expect that they are sending their students intoa non-inclusive learning environment. 7While our office recognizes all of these limitations of tutoring, we aim to provide amore inclusive tutoring space within which attendees from our target groups (womenand underrepresented minority students) can seek academic
, “Embracing Ambiguity: A Framework for Promoting IterativeDesign Thinking Approaches in Engineering and Design Curricula,” ASEE 124th AnnualConference & Exposition, Jun 25-28, 2017, Columbus, OH[13] J. Hertz, “Confidently Uncomfortable: First-year Student Ambiguity Tolerance and Self-efficacy on Open-ended Design Problems,” ASEE 125th Annual Conference & Exposition, Jun24-27, 2018, Salt Lake City, UT[14] E. Dringenberg and R. E. H. Wertz, “How do first-year engineering students experienceambiguity in engineering design problems: The development of a self-report instrument,” 2016ASEE Annual Conference & Exposition, New Orleans, Louisiana,https://doi.org/10.18260/p.25474[15] R.L. Tauritz, “How to handle knowledge uncertainty: learning and
; Singh, Granville & Dika 2002), with motivation and interest impactingmathematics and science achievement (Singh, Granville & Dika 2002; Eccles & Jacobs 1986). Itis essential, then, to consider what opportunities elementary-aged children have to develop theirbeliefs, interests, and self-efficacy related to STEM.To address the minoritization of underrepresented groups, including girls, many initiatives andinterventions have been developed through STEM programs. For elementary-aged children,these types of programs often take shape as targeted out-of-school programs. Out-of-schoolsettings represent critical opportunities for learning and broadening participation in STEM aschildren spend more than 80% of their waking hours in out-of
provide opportunities for growth in STEM of allthe participants (i.e., high school, undergraduate, and graduate student), but to alsoimprove their confidence (self-efficacy) and identity as someone who belonged in STEM. Inaddition to the professional development activities, the structure of WRAMP culminates ina team poster and presentation of the research work. With only a semester (~10-14 weeks)timeframe, much of the presentation is centered on what the HS and UG learned and thelab skills they developed (e.g., taking data, using special microscopes). They present totheir peers and parents during the WRAMP closing ceremonies. Here, the mentees shineby sharing their newly gained knowledge and skills to others. They realize how far they’vecome from
36 We hope to add more data about the demographics and admissions attributes of the students who opt to take the preLUsion LWE…. Different SAT? Is it advisable to do a pre-program assessment about their engineering identity, self efficacy? Or is this time before the semester of their first year begins not the time to ask? Would it undermine their success? What else can be done? A gauge for the success of the program might be inherently in the fact that women keep signing up for this preLUsion. ○ Is this simply a self-selecting group of excellent students? We don’t know. ○ Want to normalize our data, to determine if preLUsion women doing better than the
education: secondary testing might improve • Excessive focus ofHow prospective mathematics student scores but fail as a standardized testing asteachers grapple with teachers (PMTs) measure of teaching efficacy measure of teacher efficacyusing culturally • Predefined topics and rigid • Lack of classroom/curricularresponsive teaching instructional guides limit the autonomypractices in the age of extent to which teachers canstandardized testing
protocolapproved by the Institutional Review Board at LPI. SurveyA survey was designed to measure students’ feelings of belonging, engineering identity, and selfperceptions of math skills competence, as summarized in Table 2. These survey items had a 7-point response scale, with the exception of the math confidence (or self-efficacy) items that had a5-point scale. The survey also included additional items, but these are beyond the scope of theresearch questions explored in this paper. The pre and post surveys in 2017 and 2018 included afairly large number of items (73), with additional questions added to the post survey in fall 2018.Concerns with the length of the survey and quality of student responses led to an effort tooptimize the survey
the interviews over a three-day period in private conference rooms at the high schoolduring the participants’ regularly scheduled science or engineering courses. The teacher, amember of the research team, was aware of which students participated in the interviews,however, to protect participant confidentiality, we did not share any interview data with theteacher until after the semester had ended. Our interview protocol was developed with questionsto collect data about 1) students’ beliefs about the nature of intelligence (i.e., fixed versus growthmindset), 2) science self-efficacy, 3) career aspirations, 4) views on the gender gap in STEM,and 5) students’ beliefs about smartness. In this paper, we focus on the data collected from theportion
, and achievement. They study stereotypes, biases, campusculture, classroom experiences, identity, and sense of belonging. They identify challenges andstrategies for persistence and give recommendations on how to create interventions that supportwomen of color. The authors call on institutions to generate a sense of belonging and providesocial and structural support that increase self-efficacy. While studying experiences of women ofcolor engineering students, Tate and Linn [12] found that students formulate multiple identitiesto help them persist in engineering studies. Three identities were most prevalent: academic,social, and intellectual. Academic identity is associated with being a student and success isrepresented through grades. Social