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Engineering Students' Intelligence Beliefs and Learning

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Title: Engineering Students' Intelligence Beliefs and Learning
Language: English
Authors: Stump, Glenda S., Husman, Jenefer, Corby, Marcia
Source: Journal of Engineering Education. Jul 2014 103(3):369-387.
Availability: Wiley Periodicals, Inc. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 19
Publication Date: 2014
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: College Students, Student Attitudes, Beliefs, Engineering Education, Intelligence, Educational Attitudes, Cognitive Ability, Learning Strategies, Cooperative Learning, Self Efficacy, Grades (Scholastic), Learning Motivation
DOI: 10.1002/jee.20051
ISSN: 1069-4730
Abstract: Background: Students' beliefs about their intellectual ability influence their use of learning strategies, learning effort, and response to failure or setbacks. Students with incremental views of intelligence believe that learning is possible with sufficient effort, whereas those with entity views believe that intelligence is a fixed quality and expenditure of effort reflects an insufficient amount of that quality. Purpose: This study examined the relationship between engineering students' beliefs about intelligence and their perceived use of active learning strategies such as collaboration and knowledge-building behaviors, self-efficacy for learning and performance, and course grade. The study also examined the extent of entity and incremental beliefs in a sample of engineering students. Design/Method: The correlational study analyzed data from 377 engineering students recruited from required engineering courses at a large public university. We used bivariate correlations to examine relationships between study variables and multiple regression analyses to examine predictive ability of the variables on learning strategies and course grade. Results: Our results showed that students' intelligence beliefs were correlated with active learning strategies. Self-efficacy, reported use of collaboration, and incremental beliefs about intelligence were predictive of students' reported use of knowledge-building behaviors. Intelligence beliefs were not predictive of course grade. Conclusions: Our results demonstrate the utility of these motivational beliefs for understanding university engineering students' learning efforts. Our results also suggest a need for instructors to support incremental views of intelligence among engineering students.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1255750
Database: ERIC
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  Value: <anid>AN0096924095;6m401jul.14;2018Aug28.09:20;v2.2.500</anid> <title id="AN0096924095-1">Engineering Students' Intelligence Beliefs and Learning. </title> <p>Background: Students' beliefs about their intellectual ability influence their use of learning strategies, learning effort, and response to failure or setbacks. Students with incremental views of intelligence believe that learning is possible with sufficient effort, whereas those with entity views believe that intelligence is a fixed quality and expenditure of effort reflects an insufficient amount of that quality. Purpose: This study examined the relationship between engineering students' beliefs about intelligence and their perceived use of active learning strategies such as collaboration and knowledge ‐ building behaviors, self ‐ efficacy for learning and performance, and course grade. The study also examined the extent of entity and incremental beliefs in a sample of engineering students. Design/Method: The correlational study analyzed data from 377 engineering students recruited from required engineering courses at a large public university. We used bivariate correlations to examine relationships between study variables and multiple regression analyses to examine predictive ability of the variables on learning strategies and course grade. Results: Our results showed that students' intelligence beliefs were correlated with active learning strategies. Self ‐ efficacy, reported use of collaboration, and incremental beliefs about intelligence were predictive of students' reported use of knowledge ‐ building behaviors. Intelligence beliefs were not predictive of course grade. Conclusions: Our results demonstrate the utility of these motivational beliefs for understanding university engineering students' learning efforts. Our results also suggest a need for instructors to support incremental views of intelligence among engineering students.</p> <p>collaboration; intelligence beliefs; knowledge ‐ building behaviors</p> <p>A growing body of literature discusses individuals' theories about their own intellectual ability (e.g., Dweck, [<reflink idref="bib17" id="ref1">17</reflink>] ; Dweck & Master, [<reflink idref="bib22" id="ref2">22</reflink>] ; Mangels, Butterfield, Lamb, Good, & Dweck, [<reflink idref="bib35" id="ref3">35</reflink>] ; Reid & Ferguson, 2011). In an educational context, students' beliefs about the nature of intelligence add valuable information to the complex picture of factors that may influence success in their coursework. Beliefs that students hold about their intelligence have been shown to produce variations in their orientations to learning, efforts to learn, strategies utilized, beliefs about success, and reactions to failure (Dweck & Sorich, [<reflink idref="bib24" id="ref4">24</reflink>] ). In engineering education, increasing concerns about student learning and retention have motivated researchers to pursue possible explanations for students' academic successes and failures. As educators and researchers scrutinize students' learning behaviors in an effort to determine why those in challenging courses fail or drop out, consideration of factors in addition to behaviors seen in the classroom or knowledge gains inferred from their test scores may be fruitful. Examination of students' beliefs about themselves, or self ‐ theories, may provide important insight into their behavior. The purpose of this study was to examine the relationships between engineering students' beliefs about intelligence and their perceived use of active learning strategies such as collaboration and knowledge ‐ building behaviors, their self ‐ efficacy for learning and performance, and their course grade. In addition, we examined the extent of two types of intelligence beliefs in a sample of university engineering students.</p> <hd id="AN0096924095-2">Background</hd> <hd id="AN0096924095-3">Entity and Incremental Beliefs about Intelligence</hd> <p>Most students enter a classroom with one of two distinct conceptions of their intellectual ability. Some students believe their intelligence is a fixed trait, or an entity they possess, and that they can do nothing to change it; this belief is called an entity theory of intelligence (Dweck & Leggett, [<reflink idref="bib21" id="ref5">21</reflink>] ) or a fixed mindset (Dweck, [<reflink idref="bib19" id="ref6">19</reflink>] ). Students who adopt an entity theory of intelligence usually believe that they either “have it” or they “don't have it.” Other students believe their intelligence is malleable, or can be incrementally increased through their own efforts to learn; this belief is called an incremental theory of intelligence (Dweck & Leggett, [<reflink idref="bib21" id="ref7">21</reflink>] ) or a growth mindset (Dweck, [<reflink idref="bib19" id="ref8">19</reflink>] ). Although it was once thought that most individuals held entity beliefs regarding intellectual ability, surveys of adults and children have shown varied results: 40% of individuals typically indicate they have incremental beliefs, 40% indicate entity beliefs, and 20% are undecided (Dweck & Molden, [<reflink idref="bib23" id="ref9">23</reflink>] ).</p> <p>Researchers have found that people can hold different beliefs about their ability to change personal qualities that are dissimilar such as intelligence and moral character (Dweck, Chiu, & Hong, [<reflink idref="bib20" id="ref10">20</reflink>] ). For example, individuals may feel that they can improve their intellectual ability with avid reading and study, yet believe their moral character is unchangeable because “that is the way they are.” Similarly, researchers have found differences in students' beliefs about their intellectual ability between academic domains (Jehng, Johnson, & Anderson, [<reflink idref="bib31" id="ref11">31</reflink>] ), although there is not consensus among experts regarding these findings (Muis, [<reflink idref="bib39" id="ref12">39</reflink>] ). Schommer and her colleagues (Schommer ‐ Aikins, Duell, & Barker, [<reflink idref="bib50" id="ref13">50</reflink>] ; Schommer & Walker, [<reflink idref="bib20" id="ref14">20</reflink>] ) found that students' beliefs about their ability were similar for different academic content areas, in particular math and the social sciences. In a study that investigated general versus more specific ability beliefs, Heyman, Martyna, and Bhatia ([<reflink idref="bib29" id="ref15">29</reflink>] ) found that female engineering students and male non ‐ engineering students reported differences between beliefs about their general intellectual ability and their engineering aptitude.</p> <hd id="AN0096924095-4">Intelligence Beliefs and Approaches to Learning</hd> <hd id="AN0096924095-5">Incremental beliefs</hd> <p>Students who hold incremental beliefs tend to adopt learning goals, which focus on increasing knowledge and mastering course material (Dweck & Sorich, [<reflink idref="bib24" id="ref16">24</reflink>] ). A high IQ or history of academic achievement does not necessarily ensure adoption of these goals (Dweck, [<reflink idref="bib18" id="ref17">18</reflink>] ; Licht & Dweck, [<reflink idref="bib34" id="ref18">34</reflink>] ). Instead of focusing on past successes or a supposed index of intelligence like their IQ, students with incremental beliefs focus on increasing their knowledge. They view exertion of effort as a positive behavior, a means to becoming more intelligent (Dweck & Molden, [<reflink idref="bib23" id="ref19">23</reflink>] ), and often seek to improve their ability by selecting challenging activities and applying appropriate effort to learn (Dweck, [<reflink idref="bib17" id="ref20">17</reflink>] ; Roedel & Schraw, [<reflink idref="bib20" id="ref21">20</reflink>] ). They devote that effort to the use of deep learning strategies, such as organization and elaboration, to learn course material (Dupeyrat & Mariné, 2001). Deep learning strategies have been positively associated with academic achievement (Laird, Shoup, Kuh, & Schwarz, [<reflink idref="bib33" id="ref22">33</reflink>] ; Pressley & Harris, [<reflink idref="bib43" id="ref23">43</reflink>] ) and have also been associated with better long ‐ term retention of course material in university students (Weinstein, Husman, & Dierking, [<reflink idref="bib58" id="ref24">58</reflink>] ). Students with incremental beliefs and learning goals attribute academic successes to adequate effort. If they encounter difficulties or failure, their self ‐ efficacy, or confidence in their ability to learn and perform well in a course (Bandura, [<reflink idref="bib4" id="ref25">4</reflink>] ), is not shaken. Because they associate successful learning with effort, they take a mastery approach to the situation, attributing their difficulties to their ineffective strategies or effort and vowing to work harder (Dweck & Molden, [<reflink idref="bib23" id="ref26">23</reflink>] ).</p> <hd id="AN0096924095-6">Entity beliefs</hd> <p>On the other hand, students holding entity beliefs exhibit a less adaptive approach to learning. Because they believe their intellectual ability is innate, they worry about having enough of it. They tend to adopt performance goals, which focus on confirming or proving their ability relative to others (Dweck, [<reflink idref="bib17" id="ref27">17</reflink>] ). These students often choose easier tasks (Dweck, [<reflink idref="bib17" id="ref28">17</reflink>] ; Roedel & Schraw, [<reflink idref="bib20" id="ref29">20</reflink>] ) in order to preserve their high performance status, and also tend to exert less effort to learn. They view exertion of effort as a negative behavior, because they perceive it as a sure sign of low intelligence or inability (Dweck & Molden, [<reflink idref="bib23" id="ref30">23</reflink>] ). Students with entity beliefs often use superficial learning strategies, such as copying or rehearsal, to learn course material (Stipek & Gralinski, [<reflink idref="bib54" id="ref31">54</reflink>] ; Vermetten, Lodewijks, & Vermunt, [<reflink idref="bib57" id="ref32">57</reflink>] ). Whereas superficial strategies may be effective for learning material to be recalled, they may not help with comprehension of complex concepts such as those inherent in engineering knowledge. Students with entity beliefs often have high self ‐ efficacy for learning and performance in a course when their studies are going well, but when they encounter setbacks or failure, a different pattern of behavior emerges. These students often exhibit a helpless response (Dweck & Sorich, [<reflink idref="bib24" id="ref33">24</reflink>] ), attributing the failure to their lack of ability and telling themselves that they “just don't have it.” Instead of devoting more effort to learn the material in these situations, they often do just the opposite. In a study of junior high students, those who reported entity beliefs and had failed a test stated they would spend less time on the subject in the future, would never take the subject again, or would cheat on the next exam (Blackwell, Trzesniewski, & Dweck, [<reflink idref="bib18" id="ref34">18</reflink>] ). These reactions illustrate the complex response to failure that is often exhibited by students who believe their ability is fixed. Unlike their peers with incremental beliefs, who view failure as a sign to exert more effort, students with entity beliefs view their failure as a reflection of their low ability. They begin to doubt their capability for success, and their self ‐ efficacy for learning and performance begins to erode.</p> <p>Previous research regarding the relationship between students' theories of intelligence and approaches to learning revealed that those who held entity beliefs were less likely to report using critical thinking strategies or knowledge ‐ building behaviors such as organization and elaboration of material (Dahl, Bals, & Turi, 2005). Dupeyrat and Mariné ([<reflink idref="bib16" id="ref35">16</reflink>] ) found that students who held incremental beliefs were more likely to report using deep processing strategies. To become effective problem solvers in their chosen field, students must have an understanding of material that results from deeply processing information (Entwistle & McCune, [<reflink idref="bib26" id="ref36">26</reflink>] ; Marton & Saljo, [<reflink idref="bib36" id="ref37">36</reflink>] ). Characteristic of deep processing is an initiation by students of knowledge ‐ building behaviors, such as connecting new information to facts and ideas that are already known, searching for new related information, and constructing personal understanding of the material.</p> <p>Another approach to learning that may be affected by students' intelligence beliefs is their utilization of collaboration, or learning from peer interaction. Collaboration is another active learning strategy that has been related to increased achievement in engineering students (Prince, [<reflink idref="bib44" id="ref38">44</reflink>] ; Stump, Hilpert, Husman, Chung, & Kim, [<reflink idref="bib56" id="ref39">56</reflink>] ). Whether engaging in casual conversation after class or working together on assigned group projects, those who use collaborative learning strategies have opportunities to share ideas, challenge each other's thinking, and ultimately learn from one another (Mason, [<reflink idref="bib37" id="ref40">37</reflink>] ). Research has shown that students who feel confident in their ability to learn and perform well in a course and who actively use knowledge ‐ building strategies in their coursework also include collaboration in their repertoire of learning strategies (Husman, Lynch, Hilpert, & Duggan, 2007). Although collaboration has not been directly associated with implicit theories of intelligence in the literature, a relationship can be hypothesized. Working with one's peers demonstrates spending extra effort to learn course material, and thus it may be characteristic of those with incremental beliefs.</p> <p>Examination of this relationship between students' beliefs and their approach to learning is significant to engineering education because many students in the physical sciences report entity ‐ type beliefs (Paulsen & Wells, [<reflink idref="bib41" id="ref41">41</reflink>] ). Seymour and Hewitt ([<reflink idref="bib51" id="ref42">51</reflink>] ) found that when facing difficult courses and disappointing exam grades, engineering students who experienced failure quickly began to question their ability and their reasons for being in the engineering major. In their study of achievement ‐ related beliefs in engineering students, Heyman, Martyna, and Bhatia ([<reflink idref="bib29" id="ref43">29</reflink>] ) found that entity beliefs about engineering aptitude were reported by 100% of the female students who dropped a course after encountering difficulties. If entity beliefs are prevalent in engineering students and are associated with lower exertion of effort, suboptimal learning strategies, or lowered confidence in the face of difficulty, then the academic success or retention of these students may be jeopardized.</p> <hd id="AN0096924095-7">Intelligence Beliefs and Academic Achievement</hd> <p>Multiple studies have examined the relationship between intelligence beliefs and academic achievement in university students (Aronson, Fried, & Good, 2002; Grant & Dweck, 2003) and younger age groups (Blackwell et al., [<reflink idref="bib5" id="ref44">5</reflink>] ; Cury, Elliot, Da Fonseca, & Moller, [<reflink idref="bib14" id="ref45">14</reflink>] ; Stipek & Gralinski, [<reflink idref="bib54" id="ref46">54</reflink>] ). Grant and Dweck ([<reflink idref="bib28" id="ref47">28</reflink>] ) found that students with incremental beliefs in a college pre ‐ med chemistry course achieved higher grades than those with entity beliefs, even when controlling for SAT scores, perceived ability in chemistry, number of prior courses in chemistry, and gender as indexes of entry ability. In the study conducted by Blackwell, Trzesniewski, and Dweck ([<reflink idref="bib18" id="ref48">18</reflink>] ), intelligence beliefs of junior high students were examined in relation to their mathematics performance throughout their junior high years. They found that students who held incremental beliefs achieved progressively higher mathematics grades each semester. Most notably, this increase in performance occurred in junior high, a time in students' educational trajectory when they often exhibit a decline in motivation, school attachment, and academic performance (Eccles, Lord, & Midgley, [<reflink idref="bib25" id="ref49">25</reflink>] ). Students with entity beliefs, however, did not show improved performance over time in the same study. These students exhibited a decrease in performance over the two ‐ year period, despite the fact that they began their junior high years at the same level of achievement as their peers. Stipek and Gralinski ([<reflink idref="bib54" id="ref50">54</reflink>] ) also found that entity beliefs and their associated superficial learning strategies were related to lower achievement in older elementary students. The work that has been done across all age groups shows fairly consistent results with regard to achievement, but no studies to date have examined the relationship between ability beliefs and achievement in an engineering context.</p> <hd id="AN0096924095-8">The Present Study</hd> <p>The influence of students' beliefs about their intelligence on their learning goals, effort, strategies, and eventual academic successes suggests the importance of fully exploring them in engineering students. We argue that extending previous work by studying a university engineering student population adds to the body of literature addressing the importance of implicit theories of intelligence to student learning. Moreover, we contend that in their everyday classroom endeavors, engineering educators need to consider the intelligence beliefs of their students. This study examined the extent of entity or incremental beliefs in a sample of engineering students. We also examined the relationship between students' intelligence beliefs, active learning strategies, self ‐ efficacy for learning and performance, and achievement. More specifically, we investigated these questions:</p> <p>Which type of intelligence belief is stronger in engineering students?</p> <p>What is the relationship between the strength of students' reported intelligence beliefs and their perceived use of active learning strategies, their self ‐ efficacy for learning and performance in the course, and their course grade?</p> <p>When added to the combination of self ‐ efficacy and knowledge ‐ building behaviors, do students' reported intelligence beliefs aid in prediction of their collaborative learning strategies?</p> <p>When added to the combination of self ‐ efficacy and collaborative learning strategies, do students' reported intelligence beliefs aid in prediction of their knowledge ‐ building behaviors?</p> <p>When added to the combination of self ‐ efficacy for learning and performance and active learning strategies, do students' reported intelligence beliefs aid in prediction of their course grade?</p> <p>After our review of the literature, we hypothesized that entity beliefs may be more strongly endorsed by engineering students (Paulsen & Wells, [<reflink idref="bib41" id="ref51">41</reflink>] ). We also hypothesized that the strength of students' incremental beliefs along with their self ‐ efficacy for learning and performance would be positively related to their reported use of active learning strategies such as knowledge building (Dupeyrat & Mariné, 2001) and collaboration, and that the strength of their entity beliefs would be negatively related to those strategies (Dahl et al., [<reflink idref="bib15" id="ref52">15</reflink>] ). Lastly, we expected that a model containing all of the study variables – reported intelligence beliefs, active learning strategies, and self ‐ efficacy for learning and performance – would be predictive of students' grades in their required engineering courses.</p> <hd id="AN0096924095-9">Method</hd> <hd id="AN0096924095-10">Participants</hd> <p>The study participants were undergraduate engineering students recruited from required mechanical and aerospace engineering and electrical engineering courses at a large public university in the southwestern United States. Because students were taking multiple required courses and survey items were course ‐ specific, they had the opportunity to take multiple surveys. Initially, our data contained 845 (55%) completed surveys out of a possible 1,528. To reduce the number of surveys to one per participant, we retained only the survey taken from the lowest ‐ level course, which left 591 surveys. Surveys from the lowest ‐ level courses were retained because these courses typically enrolled large numbers of students; thus there was greater consistency of instructors and course content for study participants. Eighteen participants did not complete their respective courses after completing the survey, and their data were removed from the analysis. We eliminated surveys that could not be matched to demographic information and course grades; we also removed surveys from classes in which fewer than five students participated, in order to give us enough scores in each of the remaining classes for calculation of z ‐ scores. This process left data from 377 unique participants from 11 engineering courses for analysis. The 11 courses covered the following topics: introduction to engineering, engineering mechanics, solid mechanics, computer ‐ aided engineering, thermofluids, sensors and controls, structural mechanics, principles of mechanical design, numerical methods for engineers, high ‐ speed aerodynamics, and digital design fundamentals.</p> <p>The sample included 17.2% female students, and the participants' ages ranged from 18 to 41 years, with a mean age of 21 years. Sixteen percent of the participants were in their first year of the engineering program, 51% were in their second year, and 33% were in their third year. There were no participants in their fourth and final year. Participants reported their ethnicity as Caucasian (63%), Latino (15%), Asian (13%), American Indian or Alaska Native (less than 2%), or African American (less than 1%). Six percent of the participants did not report their ethnicity. Our sample contained 1.2% less female students, 3.6% less Caucasian students, approximately 4% less African American students, 6.5% more Latino students, and 0.8% more Asian students than the ethnic breakdown of those receiving science and engineering degrees across the United States in 2012 (Yoder, [<reflink idref="bib59" id="ref53">59</reflink>] ).</p> <hd id="AN0096924095-11">Measures</hd> <hd id="AN0096924095-12">Intelligence beliefs</hd> <p>The Implicit Theories of Intelligence Scale (Dweck, [<reflink idref="bib17" id="ref54">17</reflink>] ) is an established measure of self ‐ theories about ability. The six items in this scale assessed students' beliefs about the stability or malleability of intelligence. Example items assessing incremental and entity beliefs, respectively, are “No matter how much intelligence you have, you can always change it quite a bit” and “Your intelligence is something about you that you can't change very much.” The students responded on a Likert ‐ type scale ranging from 1 (strongly disagree) to 5 (strongly agree).</p> <hd id="AN0096924095-13">Knowledge building and collaboration</hd> <p>The Student Perceptions of Classroom Knowledge ‐ Building (SPOCK) scale (Shell et al., [<reflink idref="bib53" id="ref55">53</reflink>] ) assesses students' perceptions about their learning. Two SPOCK subscales were used in our study. These subscales have provided reliable measures of student's self ‐ reported study strategies in previous studies conducted with engineering students (Stump et al., [<reflink idref="bib55" id="ref56">55</reflink>] ). The eight ‐ item Knowledge ‐ Building subscale assessed students' self ‐ reported tendencies to construct their own understanding of classroom material. We considered high scores on this subscale as indicative of deep processing of course information. Examples of knowledge ‐ building items are “Whenever I learn something new in this class, I try to tie it to other facts and ideas that I already know” and “I try to go beyond what we are given in the lectures and text.” The five ‐ item Collaborative Learning subscale assessed students' self ‐ reported informal interaction with their classmates. Example items from this subscale are “In this class, my classmates and I actively share ideas” and “In this class, my classmates and I actively work together to learn new things.” The students responded on a Likert ‐ type scale ranging from 1 (almost never) to 5 (almost always). The subscales did not assess the professors' instructional strategies but rather student perceptions about learning classroom material. The items were classroom ‐ specific, and participants were asked to focus on only one class when responding to them.</p> <hd id="AN0096924095-14">Self ‐ efficacy for learning and performance</hd> <p>The Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich, Smith, Garcia, & McKeachie, [<reflink idref="bib42" id="ref57">42</reflink>] ) is an established scale utilized to evaluate students' motivation behaviors and their use of different study strategies. Only the eight ‐ item subscale related to self ‐ efficacy for learning and performance in a course was administered to participants in this study. Example items from this subscale are “I am confident I can understand the basic concepts taught in this course” and “Considering the difficulty of this course, the teacher, and my skills, I think I will do well in this course.” The students responded on a Likert ‐ type scale ranging from 1 (not at all true of me) to 7 (very true of me).</p> <hd id="AN0096924095-15">Course grade</hd> <p>Students' course grades were retrieved from the university registrar's office and included in the data. Grades were measured on a four ‐ point plus or minus scale. The highest possible grade was an A+ (4.33) and the lowest possible grade was no credit (0.00).</p> <hd id="AN0096924095-16">Procedure</hd> <p>Data for the current study were obtained in the spring and fall of 2008 via a survey administered either in ‐ class or online. Students were informed about the survey verbally by research assistants if it was administered in ‐ class or by course website announcements and faculty e ‐ mail if it was available to them online. Students who took the survey in class did so at a time designated by their instructors, and those who took it online could take it at their convenience. All participants received a monetary incentive of 10 dollars for their participation. Course grades and demographic data were obtained from the university registrar.</p> <hd id="AN0096924095-17">Analysis</hd> <p>To maintain the statistical assumption of independence, we eliminated extra surveys from students who took the survey in more than one of the 11 surveyed courses. Scale scores for the variables of interest (intelligence beliefs, knowledge building, collaboration, and self ‐ efficacy for learning and performance) were created for each student by calculating a mean score from the respective items contained in each of the scales. Scores from the Implicit Theories of Intelligence scale were divided into two subscale scores, incremental beliefs and entity beliefs. We used listwise deletion for missing values in the dataset. Descriptive statistics were completed on the data and examined. Coefficient alpha (Cronbach, [<reflink idref="bib13" id="ref58">13</reflink>] ) was computed on each subscale to obtain reliability evidence.</p> <p>To answer the first research question regarding differences in the strength of incremental or entity beliefs in the engineering student sample, we conducted a dependent samples t ‐ test (Coladarci, Cobb, Minium, & Clarke, 2004). To eliminate differences in reported scores that may have resulted from course or instructor influence, we then converted scale scores and course grade points to z ‐ scores by course and instructor to preserve within ‐ group position but remove between ‐ course or instructor differences (Coladarci et al., [<reflink idref="bib10" id="ref59">10</reflink>] ). To answer our second research question related to understanding the relationship between students' reported intelligence beliefs and their perceived use of active learning strategies, self ‐ efficacy for learning and performance in the course, and course grade, we computed Pearson product ‐ moment correlation coefficients (Cohen, Cohen, West, & Aiken, 2003) among the study variables. For further exploration of variable relationships to answer the remaining research questions, we conducted multiple regression analyses (Cohen et al., [<reflink idref="bib9" id="ref60">9</reflink>] ). We first examined the predictive ability of intelligence beliefs, knowledge ‐ building behaviors, and self ‐ efficacy on students' reported collaboration to answer our third research question, and then examined the predictive ability of intelligence beliefs, collaboration, and self ‐ efficacy on their reported knowledge ‐ building behaviors to answer the fourth research question. We conducted a third multiple regression analysis to examine the predictive ability of intelligence beliefs, self ‐ efficacy, and active learning strategies on students' course grade to answer our fifth research question.</p> <hd id="AN0096924095-18">Results</hd> <p>Descriptive statistics showed that the data met assumptions required for the intended analyses (see Table). Coefficient alphas (Cronbach, [<reflink idref="bib13" id="ref61">13</reflink>] ) for the subscales were as follows: incremental beliefs   =   0.93, entity beliefs   =   0.83, collaborative learning   =   0.94, knowledge ‐ building   =   0.88, and self ‐ efficacy   =   0.94.</p> <p>Descriptive Statistics for All Variables</p> <p> <ephtml> <table><tr><th align="left" /><th align="center" /><th align="center" /><th align="center">Range</th><th align="center" /></tr><tr><th align="left" /><th align="center">M</th><th align="center">SD</th><th align="center">Potential</th><th align="center">Actual</th><th align="center">Skew</th></tr><tr><td align="left">Incremental beliefs</td><td align="char" char=".">3.44</td><td align="char" char=".">0.99</td><td align="char" char="–">1–5</td><td align="char" char=".">1.0–5.0</td><td align="char" char=".">−0.37</td></tr><tr><td align="left">Entity beliefs</td><td align="char" char=".">2.57</td><td align="char" char=".">0.97</td><td align="char" char="–">1–5</td><td align="char" char=".">1.0–5.0</td><td align="char" char=".">0.26</td></tr><tr><td align="left">Knowledge ‐ building behaviors</td><td align="char" char=".">3.40</td><td align="char" char=".">0.73</td><td align="char" char="–">1–5</td><td align="char" char=".">1.0–5.0</td><td align="char" char=".">−0.50</td></tr><tr><td align="left">Collaborative learning strategies</td><td align="char" char=".">3.11</td><td align="char" char=".">1.13</td><td align="char" char="–">1–5</td><td align="char" char=".">1.0–5.0</td><td align="char" char=".">−0.22</td></tr><tr><td align="left">Self ‐ efficacy</td><td align="char" char=".">5.47</td><td align="char" char=".">1.09</td><td align="char" char="–">1–7</td><td align="char" char=".">1.5–7.0</td><td align="char" char=".">−0.65</td></tr><tr><td align="left">Course grade</td><td align="char" char=".">2.96</td><td align="char" char=".">0.99</td><td align="char" char="–">0–4.3</td><td align="char" char=".">0.0–4.3</td><td align="char" char=".">−1.08</td></tr></table> </ephtml> </p> <p>1 Note: Listwise N   =   372.</p> <p>The dependent samples t ‐ test, completed to answer the first research question, showed that on average, engineering students' incremental beliefs (M   =   3.44) were significantly stronger than their entity beliefs, M   =   2.58, t (<reflink idref="bib373" id="ref62">373</reflink>)   =   9.14, p   <   0.001.</p> <p>The bivariate correlational analysis (see Table), completed to answer the second research question, revealed a significant positive correlation between the strength of students' incremental beliefs and reported knowledge ‐ building behaviors as well as collaboration (r   =   0.22, p   <   0.001; r   =   0.12, p   =   0.022, respectively). Conversely, the strength of their entity beliefs was negatively related to students' reported knowledge ‐ building behaviors and collaboration (r   =   –0.19, p   <   0.001; r   =   −0.10, p   =   0.048, respectively), and neither of the two intelligence beliefs was significantly related to students' confidence for learning and performance or their course grades. However, students' reported knowledge ‐ building behaviors and collaborative strategies were positively correlated, and both approaches were positively correlated with students' self ‐ efficacy for learning and performance and their grade in the course.</p> <p>Correlations between Study Variables</p> <p> <ephtml> <table><tr><th align="left">Measure</th><th align="center">1</th><th align="center">2</th><th align="center">3</th><th align="center">4</th><th align="center">5</th></tr><tr><td align="char" char=".">1. Incremental beliefs</td><td align="center">–</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="char" char=".">2. Entity beliefs</td><td align="char" char=".">−0.75</td><td align="center">–</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="char" char=".">3. Knowledge ‐ building behaviors</td><td align="char" char=".">0.22</td><td align="char" char=".">−0.19</td><td align="center">–</td><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="char" char=".">4. Collaborative learning strategies</td><td align="char" char=".">0.12</td><td align="char" char=".">−0.10</td><td align="char" char=".">0.37</td><td align="center">–</td><td align="char" char="." /></tr><tr><td align="char" char=".">5. Self ‐ efficacy</td><td align="char" char=".">−0.02</td><td align="char" char=".">−0.08</td><td align="char" char=".">0.31</td><td align="char" char=".">0.13</td><td align="center">–</td></tr><tr><td align="char" char=".">6. Course grade</td><td align="char" char=".">−0.06</td><td align="char" char=".">−0.03</td><td align="char" char=".">0.13</td><td align="char" char=".">0.13</td><td align="char" char=".">0.44</td></tr></table> </ephtml> </p> <ulist> <item>2 Note: Listwise N   =   372.</item> <item>3 p   <   0.05;</item> <item>4 **p   <   0.01.</item> </ulist> <p>Results of the first multiple regression analysis, completed to answer the third research question, showed that the linear combination of students' reported self ‐ efficacy, knowledge ‐ building behaviors, incremental beliefs, and entity beliefs was predictive of their reported collaboration, F(<reflink idref="bib4" id="ref63">4</reflink>,<reflink idref="bib367" id="ref64">367</reflink>)   =   14.75, p   <   0.001, adj. R<sups>2</sups>   =   0.13, but the only significant predictor within that combination was knowledge ‐ building behaviors (see Table).</p> <p>Predictors of Collaborative Learning Strategies</p> <p> <ephtml> <table><tr><th align="left">Variable</th><th align="center">Model R<sup>2</sup></th><th align="center">R<sup>2</sup><sub>adj.</sub></th><th align="center">B</th><th align="center">SEB</th><th align="center">sr<sup>2</sup></th></tr><tr><td align="left" /><td align="char" char=".">0.14</td><td align="char" char=".">0.13</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="left">Intercept</td><td align="char" char="." /><td align="char" char="." /><td align="center">–</td><td align="char" char=".">0.05</td><td align="char" char="." /></tr><tr><td align="left">Self ‐ efficacy</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.02</td><td align="char" char=".">0.05</td><td align="center">–</td></tr><tr><td align="left">Knowledge ‐ building behaviors</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.35</td><td align="char" char=".">0.05</td><td align="char" char=".">0.11</td></tr><tr><td align="left">Incremental beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.04</td><td align="char" char=".">0.08</td><td align="center">–</td></tr><tr><td align="left">Entity beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">−0.01</td><td align="char" char=".">0.08</td><td align="center">–</td></tr></table> </ephtml> </p> <ulist> <item>5 Note: Listwise N   =   372. B   =   standardized Beta coefficient; SEB   =   standard error of the Beta coefficient; sr2   =   squared semi ‐ partial correlation.</item> <item>6 p   <   0.01.</item> </ulist> <p>A second multiple regression analysis, completed to answer the fourth research question, showed that students' reported self ‐ efficacy, perceived collaboration, incremental beliefs, and entity beliefs were predictive of their self ‐ reported knowledge ‐ building behaviors, F(<reflink idref="bib4" id="ref65">4</reflink>,<reflink idref="bib367" id="ref66">367</reflink>)   =   29.40, p   <   0.001, adj. R<sups>2</sups>   =   0.23. After removing the one nonsignificant predictor – entity beliefs – from the model, the linear combination of self ‐ efficacy, collaboration, and incremental beliefs accounted for 24% of the variance in students' self ‐ reported knowledge ‐ building behaviors, F(<reflink idref="bib3" id="ref67">3</reflink>,<reflink idref="bib369" id="ref68">369</reflink>)   =   39.35, p   <   0.001, adj. R<sups>2</sups>   =   0.24, with incremental beliefs accounting for 3% of the total variance (see Table).</p> <p>Predictors of Knowledge ‐ Building Behaviors</p> <p> <ephtml> <table><tr><th align="left">Variable</th><th align="center">Model R<sup>2</sup></th><th align="center">R<sup>2</sup><sub>adj.</sub></th><th align="center">B</th><th align="center">SEB</th><th align="center">sr<sup>2</sup></th></tr><tr><td align="left">Model 1</td><td align="char" char=".">0.24</td><td align="char" char=".">0.23</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="left">Intercept</td><td align="char" char="." /><td align="char" char="." /><td align="center">–</td><td align="char" char=".">0.04</td><td align="char" char="." /></tr><tr><td align="left">Self ‐ efficacy</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.28</td><td align="char" char=".">0.05</td><td align="char" char=".">0.07</td></tr><tr><td align="left">Collaborative learning strategies</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.31</td><td align="char" char=".">0.05</td><td align="char" char=".">0.09</td></tr><tr><td align="left">Incremental beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.20</td><td align="char" char=".">0.07</td><td align="char" char=".">0.02</td></tr><tr><td align="left">Entity beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.01</td><td align="char" char=".">0.07</td><td align="center">–</td></tr><tr><td align="left">Model 2</td><td align="char" char=".">0.24</td><td align="char" char=".">0.24</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="left">Intercept</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.01</td><td align="char" char=".">0.04</td><td align="char" char="." /></tr><tr><td align="left">Self ‐ efficacy</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.28</td><td align="char" char=".">0.05</td><td align="char" char=".">0.07</td></tr><tr><td align="left">Collaborative learning strategies</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.31</td><td align="char" char=".">0.05</td><td align="char" char=".">0.09</td></tr><tr><td align="left">Incremental beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.19</td><td align="char" char=".">0.05</td><td align="char" char=".">0.03</td></tr></table> </ephtml> </p> <ulist> <item>7 Note: Listwise N   =   372. B   =   standardized Beta coefficient; SEB   =   standard error of the Beta coefficient; sr2   =   squared semi ‐ partial correlation.</item> <item>8 p   <   0.01.</item> </ulist> <p>In answer to the fifth research question, a third multiple regression analysis using course grade as the dependent variable showed that only students' self ‐ efficacy for learning and performance in the course was a significant predictor (see Table). Although the p ‐ values for collaboration and incremental beliefs were low, 0.085 and 0.082, respectively, they did not meet our established criteria for significance.</p> <p>Predictors of Course Grade</p> <p> <ephtml> <table><tr><th align="left">Variable</th><th align="center">Model R<sup>2</sup></th><th align="center">R<sup>2</sup><sub>adj</sub>.</th><th align="center">B</th><th align="center">SEB</th><th align="center">sr<sup>2</sup></th></tr><tr><td align="left" /><td align="char" char=".">0.21</td><td align="char" char=".">0.20</td><td align="char" char="." /><td align="char" char="." /><td align="char" char="." /></tr><tr><td align="left">Intercept</td><td align="char" char="." /><td align="char" char="." /><td align="center">–</td><td align="char" char=".">0.05</td><td align="char" char="." /></tr><tr><td align="left">Self ‐ efficacy</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.43</td><td align="char" char=".">0.05</td><td align="char" char=".">0.16</td></tr><tr><td align="left">Collaborative learning strategies</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">0.09</td><td align="char" char=".">0.05</td><td align="center">–</td></tr><tr><td align="left">Knowledge ‐ building behaviors</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">−0.03</td><td align="char" char=".">0.05</td><td align="center">–</td></tr><tr><td align="left">Incremental beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">−0.13</td><td align="char" char=".">0.07</td><td align="center">–</td></tr><tr><td align="left">Entity beliefs</td><td align="char" char="." /><td align="char" char="." /><td align="char" char=".">−0.09</td><td align="char" char=".">0.07</td><td align="center">–</td></tr></table> </ephtml> </p> <ulist> <item>9 Note: Listwise N   =   372. B   =   standardized Beta coefficient; SEB   =   standard error of the Beta coefficient; sr2   =   squared semi ‐ partial correlation.</item> <item>10 p   <   0.01.</item> </ulist> <hd id="AN0096924095-19">Discussion</hd> <p>In this study, we examined entity and incremental beliefs about intelligence in a sample of engineering students. Additionally, we examined the relationships between students' reported intelligence beliefs and their confidence to learn and perform well in their course, self ‐ reported active learning strategies, and course achievement. There are several limitations to this study that should be acknowledged. With the exception of course grade, our data was self ‐ reported by students, and we did not have access to information regarding their actual collaborative or knowledge ‐ building behaviors. Additionally, our sampling frame consisted of engineering students from one university, which could limit the generalizability of our findings. Nonetheless, we argue that our results can be generalized to engineering programs within large, public institutions that serve diverse student populations.</p> <p>Our research questions focused on (<reflink idref="bib1" id="ref69">1</reflink>) the type of intelligence beliefs more strongly held by a sample of engineering students, (<reflink idref="bib2" id="ref70">2</reflink>) the relationship between students' intelligence beliefs, self ‐ efficacy for learning and performance, use of active learning strategies, and course grade, (<reflink idref="bib3" id="ref71">3</reflink>) the predictive ability of students' intelligence beliefs, their self ‐ efficacy for learning and performance in their course, and knowledge ‐ building behaviors on collaborative learning strategies, (<reflink idref="bib4" id="ref72">4</reflink>) the predictive ability of students' intelligence beliefs, their self ‐ efficacy for learning and performance in their course, and collaborative learning strategies on their knowledge ‐ building behaviors, and (<reflink idref="bib5" id="ref73">5</reflink>) the predictive ability of the aforementioned variables on their course grade.</p> <p>For the first research question, our results regarding the endorsement of incremental beliefs in university engineering students did not match our expectations. Although past research has reported that many students in disciplines such as engineering possess entity beliefs (Paulsen & Wells, [<reflink idref="bib41" id="ref74">41</reflink>] ), we did not find that to be the case. In our sample, engineering students' incremental beliefs were, on average, significantly stronger than their entity beliefs. However, a review of our sample composition revealed that approximately 84% of the participants were drawn from upper ‐ level courses, which may have affected these results. Reid and Ferguson ([<reflink idref="bib45" id="ref75">45</reflink>] ) found that freshman engineering students entered their first year of study with higher levels of entity beliefs, or a more fixed mindset, than first ‐ year business students. Their work also showed that engineering students even reported a slight increase in entity beliefs as they were completing the coursework required in the first year of the engineering curriculum. In our case, it is possible that students who entered the engineering curriculum with strong entity beliefs may have already encountered failure and chosen not to persist beyond the freshman year. Future studies should investigate the intelligence beliefs of students upon entry into the engineering major along with changes that may occur as they complete their coursework.</p> <p>Our results did match our expectations for the second research question, however, revealing a significant relationship between the extent of engineering students' incremental beliefs and self ‐ reported active learning strategies. Students who reported stronger incremental beliefs, or that intelligence is malleable, were more likely to report engaging in knowledge ‐ building behaviors and collaboration – behaviors that are related to deep learning of course material. In contrast, engineering students who reported stronger entity beliefs, or that intelligence is fixed, were significantly less likely to engage in knowledge ‐ building behaviors or collaborative learning strategies in their respective courses.</p> <p>Our study results did not show a significant relationship between intelligence beliefs and students' self ‐ efficacy for learning course material or performing well in the course. The lack of direct association between either type of intelligence belief and self ‐ efficacy is not surprising, given their theoretical relationship. Dweck ([<reflink idref="bib17" id="ref76">17</reflink>] ) explained that high self ‐ efficacy can be found in students with either type of intelligence beliefs, and that the level of self ‐ efficacy they bring to a situation is not as important as their ability to maintain that confidence when setbacks occur, since maintaining confidence is more difficult for students holding entity beliefs. Because they worry about confirming or proving their ability relative to others, students with strong entity beliefs often allow poor performance to decrease their self ‐ efficacy. Their low self ‐ efficacy can trigger the helpless response described earlier, or they may attempt to maintain their earlier self ‐ efficacy for task performance by choosing to engage in easier tasks. Students with incremental beliefs may also experience lower self ‐ efficacy when they perform poorly, but they continue to focus on mastery of the material and use their poor performance as an incentive to devote more effort to learning. Our sample most likely contained students with varied levels of self ‐ efficacy, which may have resulted from any of the above identified reasons. Further exploration of the relationship between intelligence beliefs and self ‐ efficacy is needed to determine how students' beliefs interact with high or low levels of self ‐ efficacy to influence their learning behaviors and performance as they encounter difficulties in their coursework.</p> <p>For our third research question, despite significant correlations between the variables, incremental beliefs, entity beliefs, and self ‐ efficacy for learning and performance did not predict students' use of collaboration as a means to increase their learning. In our sample, only students' reported use of knowledge ‐ building behaviors was significantly predictive of their use of collaborative learning strategies. The close relationship between these active learning strategies has been reported in other work (e.g., Husman et al., [<reflink idref="bib30" id="ref77">30</reflink>] ; Shell et al., [<reflink idref="bib53" id="ref78">53</reflink>] ; Stump et al., [<reflink idref="bib55" id="ref79">55</reflink>] ) and thus, is not surprising.</p> <p>Students' reported self ‐ efficacy for learning and performance, collaborative learning strategies, and incremental beliefs were, however, significantly predictive of their use of knowledge ‐ building behaviors. Students who were confident in their ability to learn, used collaboration as a means to learn, and believed that learning could be improved with effort over time tended to use strategies that promoted deep conceptual learning.</p> <p>Students' intelligence beliefs, their self ‐ efficacy for learning and performance, and their use of active learning strategies were not predictive of their course grades as we hypothesized in our fifth research question. One difficulty in establishing predictive relationships between these variables in any given course is that there are many self ‐ regulatory and motivational behaviors that also influence students' performance (Shell & Husman, [<reflink idref="bib52" id="ref80">52</reflink>] ). These additional factors may serve as mediators and make it difficult to establish the direct relationships between intelligence beliefs and performance that we hypothesized. Also, as previous studies have shown (Aronson et al., [<reflink idref="bib3" id="ref81">3</reflink>] ; Blackwell et al., [<reflink idref="bib5" id="ref82">5</reflink>] ), the effect of intelligence beliefs on performance may become more evident if these variables are evaluated longitudinally. Longitudinal analysis would allow time to note the effect of deep learning strategies on retention and utilization of learned information. Another limitation of our study related to this finding is that the intelligence belief items were general in nature, rather than specific to learning engineering content. This potential difference between students' general ability beliefs and more specific engineering ‐ related beliefs, as illustrated by the work of Heyman et al. ([<reflink idref="bib29" id="ref83">29</reflink>] ), may have also contributed to our null result. This is an area for further study.</p> <p>Despite the lack of direct relationship between students' ability beliefs and course grade, the strength of their incremental beliefs was significantly correlated with and predictive of their knowledge ‐ building behaviors – active learning strategies that were correlated with course grade. Similarly, the strength of students' incremental beliefs was significantly correlated with their collaborative learning behaviors – also active learning strategies that were correlated with course grade. The positive association between students' self ‐ theories and their active learning strategies is significant and should still stimulate thought among engineering educators about how these beliefs develop and how educators might cultivate or nurture adaptive ones in their students.</p> <p>Although researchers believe that early intelligence beliefs are fostered by parental behaviors (Dweck, [<reflink idref="bib17" id="ref84">17</reflink>] ), students' beliefs about their ability are also influenced by others who encourage students to pursue STEM careers (Seymour & Hewitt, 2000). High school teachers and counselors may innocently perpetuate entity beliefs by referring to students' mathematics and science ability as a talent they possess rather than emphasizing students' strategy use, effort, or self ‐ regulation as positive attributes. When making the choice to become an engineer, many students report being told that they were good in math and science and that this ability would make them good candidates for the profession (Seymour & Hewitt, 2000). These types of statements support the “have it” or “don't have it” view of ability. If students later encounter difficulties or failure along their educational paths, they may be left without confidence in their ability to succeed because they may feel that for some reason, they just do not “have it” any longer. Despite the finding that students in our sample had stronger incremental than entity beliefs, there were still students holding on to entity beliefs who may be vulnerable to this sequence of events.</p> <p>At the university level, interventions may seem too late to undo students' conceptions about ability developed and reinforced since early childhood, but studies have shown that change can occur at different points over one's life span and that small interventions do indeed make a difference. Dweck and her colleagues provided evidence that instructors and organizations can support incremental beliefs in their students or adult employees (Blackwell et al., [<reflink idref="bib5" id="ref85">5</reflink>] ; Dweck & Master, 2009; Murphy & Dweck, [<reflink idref="bib40" id="ref86">40</reflink>] ). The work of Aronson et al. ([<reflink idref="bib3" id="ref87">3</reflink>] ) pointed out the value not only of having students learn about incremental views of intelligence, but of developing ways to inspire students to advocate and reflect on them. In that study, university students who advocated the incremental theory of intelligence to others also integrated it into their own thinking and retained their views over time. There is still much work to be done to understand effective ways of promoting strong incremental beliefs in students.</p> <hd id="AN0096924095-20">Implications for Engineering Education</hd> <p>Our results that reveal the role played by incremental beliefs in knowledge ‐ building behaviors lend some credence to instructors' practice of encouraging incremental beliefs in their students. This practice may go hand ‐ in ‐ hand with those that promote student retention in science and engineering programs in general. A recent meta ‐ analysis (Geisinger & Raman, [<reflink idref="bib27" id="ref88">27</reflink>] ) of studies examining factors related to student retention in engineering programs identified that the classroom and academic climate were important. More specifically, the authors found that lack of personal encouragement and attention from instructors as well as a competitive classroom environment were key considerations when students choose to leave the major. To create and maintain a supportive classroom environment, instructors must inherently believe that all students have the ability to increase their intelligence. Their discourse and teaching practices must then help their students to understand that by immersing themselves in certain experiences and cooperative activities, intellectual ability is malleable.</p> <p>One of the most effective tools instructors have for influencing students' perceptions about their own ability is praise or feedback (Mueller & Dweck, [<reflink idref="bib38" id="ref89">38</reflink>] ). These messages can create and reinforce students' perception that their ability is fixed or alternatively can provide students with an understanding of the ways in which their ability can grow over time. In his extensive study of student ‐ instructor interactions, Brophy ([<reflink idref="bib7" id="ref90">7</reflink>] ) noted that praise or feedback delivered contingently and specific to the particulars of the accomplishment (provides specific information about students' effort or successful behaviors in relation to task difficulty) is most likely to produce an optimal motivational orientation. This type of praise is process oriented (Cimpian, Arce, Markman, & Dweck, [<reflink idref="bib18" id="ref91">18</reflink>] ; Kamins & Dweck, [<reflink idref="bib24" id="ref92">24</reflink>] ). Alternatively, praise or feedback that is outcome oriented (provides very little or nonspecific information, i.e., a grade, a “good job” comment) or person oriented (emphasizes the importance of ability, natural talent, or external factors, i.e., luck or easy task) may be debilitating to students' motivation. Communication that emphasizes students' intellectual ability (e.g., “you're a genius”) also promotes the idea that ability is innate and supports students' entity beliefs, whereas communication that acknowledges their effort and successful strategies for learning is much more likely to nurture incremental beliefs, that they have a continuing ability to learn (Dweck, [<reflink idref="bib19" id="ref93">19</reflink>] ).</p> <p>Covington and Omelich ([<reflink idref="bib11" id="ref94">11</reflink>] ), however, argued that in the context of a society that values innate intellectual ability, recognition of effort can serve as a double ‐ edged sword, particularly if it is mixed with praise for ability. When students are praised for their effort by instructors who readily acknowledge other students as having natural ability, students perceive the praise for effort as an indication that they must lack natural ability. This line of reasoning suggests that instructors should provide students with praise that is specific to good strategies or focused on effort and refrain from praising any students for their innate abilities.</p> <p>A classroom milieu emphasizing ability and performance is a possible reason why students with entity beliefs who have been successful in mathematics and science during their short academic careers may resort to cheating or simply give up when they come across difficult or challenging content. Anderman and his colleagues provided evidence that the amount of cheating behaviors adolescents reported was related to their exposure to instructional environments in which there was a focus on performance and ability (Anderman, Griesinger, & Westerfield, [<reflink idref="bib1" id="ref95">1</reflink>] ; Anderman & Midgley, [<reflink idref="bib2" id="ref96">2</reflink>] ). Blackwell et al. ([<reflink idref="bib5" id="ref97">5</reflink>] ) found that junior high students with entity beliefs were willing to cheat in order to maintain an appearance of high ability. In an engineering context, if learning course material requires students to put forth maximal time and effort, they may interpret this requirement as evidence that they do not have the ability required to become an engineer and will never be successful without resorting to cheating behaviors. Instructors at all levels need to carefully tailor their conversation, feedback, and praise to emphasize that effort and strategic learning practices are integral to successful student outcomes in their courses.</p> <p>Strategies that may reduce entity beliefs in the classroom include ones that direct students' focus toward improving their ability instead of noting their performance relative to other students (Dweck & Master, 2009; Rheinberg, Vollmeyer, & Rollett, 2000). As an alternative to posting exam grades, instructors could direct students to track their own scores on tests or quizzes and note personal improvement related to various learning strategies. Instructors can help students attribute failures to their lack of effort ‐ based strategies by asking questions such as “How do you study for this type of exam?” or “How long do you study each day (or week)?” Similarly, instructors can help students attribute their academic successes to positive behaviors and effort ‐ based strategies by asking questions such as “What learning strategy did you find most helpful for this test?” or “How long did you spend studying for this quiz?” Students should be encouraged to record the learning strategies they use, along with their resultant success on exams, as a means to help them recognize the value of effort ‐ based strategies to their academic success.</p> <p>Engineering instructors can also help to shape students' beliefs about intelligence by illustrating the important relationship between effort and learning in their own lives and in the lives of others. Students with entity beliefs may think that faculty members are natural geniuses in their domain of expertise. Dweck ([<reflink idref="bib19" id="ref98">19</reflink>] ) recommended that faculty should portray experts in the field as those who have worked hard to learn and understand the content rather than as individuals who have been gifted with innate ability. By giving specific examples about times when they themselves had to exert large amounts of effort to master a topic or procedure, instructors can help students to understand that expertise is not something one is born with.</p> <p>Moreover, instructors can incorporate examples of strategies that reflect increased effort into class discussion at the beginning of the semester or prior to exams. They can point out specific strategies that they found helpful when they were learning difficult course material (e.g., teaching another classmate, making notecards, paraphrasing the teacher's ideas in their notes). Telling stories about former students who struggled in the course, modified their level of effort or study strategies, and eventually succeeded affirms that these efforts can lead to increased learning and increased ability. Instructors may also suggest that students talk with peers who were former students to discover what learning or study strategies proved to be successful for the class; this suggestion could be included on the course syllabus as an assignment.</p> <p>When discussing coursework and effort required to be successful in a course, instructors have an excellent opportunity to inculcate incremental beliefs in their students. At this point, they can emphasize to students that course material is difficult yet within their grasp, and that learning will occur if they expend adequate effort. Schommer ([<reflink idref="bib48" id="ref99">48</reflink>] ) recommended explicitly telling students that higher ‐ level learning is challenging and requires intense effort, that the ensuing struggle to learn course material is bound to produce unpleasant emotions, and that facing a difficult task should be viewed as a challenge rather than as a potential failure. She added that students should be encouraged to work harder and attempt multiple strategies to meet their goals. Schommer also recommended assigning complex problems that have no clear ‐ cut answers to provide opportunities for such experiences. Instructor support that includes identification of acceptable answers as students tackle these types of challenges will foster the idea that expenditure of effort can result in success.</p> <p>Another related approach might be to share with students some of the findings from neuroscience research about the brain's continued capacity for learning throughout the lifespan (Boyke, Driemeyer, Gaser, Buchel, & May, 2008; Cozolino & Sprokay, [<reflink idref="bib12" id="ref100">12</reflink>] ). Recent studies have shown that the human brain has the capability to change structure on the basis of experiences (Boyke et al., [<reflink idref="bib6" id="ref101">6</reflink>] ). In their intervention studies, Dweck and colleagues teach students that their brains make new connections every time they learn and that over time, they can increase their intelligence through their efforts (e.g., Blackwell et al., [<reflink idref="bib5" id="ref102">5</reflink>] ). Instructors could discuss difficult assignments as valuable opportunities for continued learning.</p> <p>In conclusion, we argue that engineering educators need to be cognizant of the work related to intelligence beliefs and mindful of the ways they can foster adaptive beliefs in their students. Although seemingly simple, the above interventions may provide significant returns toward students' approach to learning in the classroom.</p> <hd id="AN0096924095-21">Acknowledgments</hd> <p>Funding for the present study was provided by National Science Foundation grant REC ‐ 0546856, CAREER: Connecting with the Future: Supporting Career and Identity Development in Post ‐ Secondary Science and Engineering. This article was based on “Student Beliefs abouts Intelligence: Relationship to Learning” by Stump, Husman, Chung, & Done ([<reflink idref="bib55" id="ref103">55</reflink>] ), which was published in proceedings from the Frontiers in Education annual meeting held in San Antoxio, Texas, in 2009. © 2009 IEEE. No copyrighted material from other sources has been used or adapted.</p> <p>The authors gratefully acknowledge the assistance of Wen ‐ ting Chung and Aaron Done in reviewing an initial version of this work, as well as anonymous reviewers for their comprehensive and thoughtful commentary on this manuscript prior to revisions.</p> <ref id="AN0096924095-22"> <title>References</title> <blist> <bibl id="bib1" idref="ref69" type="bt">1</bibl> <bibtext>Anderman, E. M., Griesinger, T., & Westerfield, G. (1998). Motivation and cheating during early adolescence. 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Stump is Associate Director for Education Research in the Teaching and Learning Laboratory at the Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139;.</p> <p>Jenefer Husman is an associate professor in the T. Denny Sanford School of Social and Family Dynamics and the Director of Education for QESST Engineering Research Center at Arizona State University, Tempe, AZ 85287;.</p> <p>Marcia Corby is an instructor of mathematics at Phoenix College, 1202 West Thomas Road, Phoenix, AZ 85013;.</p> </aug> <nolink nlid="nl1" bibid="bib373" firstref="ref62"></nolink> <nolink nlid="nl2" bibid="bib367" firstref="ref64"></nolink> <nolink nlid="nl3" bibid="bib369" firstref="ref68"></nolink>
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  Data: 2014
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Beliefs%22">Beliefs</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+Education%22">Engineering Education</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligence%22">Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Attitudes%22">Educational Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Ability%22">Cognitive Ability</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Strategies%22">Learning Strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Grades+%28Scholastic%29%22">Grades (Scholastic)</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Motivation%22">Learning Motivation</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jee.20051
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1069-4730
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Students' beliefs about their intellectual ability influence their use of learning strategies, learning effort, and response to failure or setbacks. Students with incremental views of intelligence believe that learning is possible with sufficient effort, whereas those with entity views believe that intelligence is a fixed quality and expenditure of effort reflects an insufficient amount of that quality. Purpose: This study examined the relationship between engineering students' beliefs about intelligence and their perceived use of active learning strategies such as collaboration and knowledge-building behaviors, self-efficacy for learning and performance, and course grade. The study also examined the extent of entity and incremental beliefs in a sample of engineering students. Design/Method: The correlational study analyzed data from 377 engineering students recruited from required engineering courses at a large public university. We used bivariate correlations to examine relationships between study variables and multiple regression analyses to examine predictive ability of the variables on learning strategies and course grade. Results: Our results showed that students' intelligence beliefs were correlated with active learning strategies. Self-efficacy, reported use of collaboration, and incremental beliefs about intelligence were predictive of students' reported use of knowledge-building behaviors. Intelligence beliefs were not predictive of course grade. Conclusions: Our results demonstrate the utility of these motivational beliefs for understanding university engineering students' learning efforts. Our results also suggest a need for instructors to support incremental views of intelligence among engineering students.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1255750
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1255750
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/jee.20051
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 369
    Subjects:
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Beliefs
        Type: general
      – SubjectFull: Engineering Education
        Type: general
      – SubjectFull: Intelligence
        Type: general
      – SubjectFull: Educational Attitudes
        Type: general
      – SubjectFull: Cognitive Ability
        Type: general
      – SubjectFull: Learning Strategies
        Type: general
      – SubjectFull: Cooperative Learning
        Type: general
      – SubjectFull: Self Efficacy
        Type: general
      – SubjectFull: Grades (Scholastic)
        Type: general
      – SubjectFull: Learning Motivation
        Type: general
    Titles:
      – TitleFull: Engineering Students' Intelligence Beliefs and Learning
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Stump, Glenda S.
      – PersonEntity:
          Name:
            NameFull: Husman, Jenefer
      – PersonEntity:
          Name:
            NameFull: Corby, Marcia
    IsPartOfRelationships:
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          Dates:
            – D: 01
              M: 07
              Type: published
              Y: 2014
          Identifiers:
            – Type: issn-print
              Value: 1069-4730
          Numbering:
            – Type: volume
              Value: 103
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Journal of Engineering Education
              Type: main
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