Abstract:Using data on upper-division students in the University of California system, we show that two distinct cultures of engagement exist on campus. The culture of engagement in the arts, humanities and social sciences focuses on interaction, participation, and interest in ideas. The culture of engagement in the natural sciences and engineering focuses on improvement of quantitative skills through collaborative study with an eye to rewards in the labor market. The two cultures of engagement are strongly associated … Show more
“…If students can see the value of the work, they will put forth the effort in completing the learning task (applied expectancy theory). Results of the repeated measures are aligned with the literature indicating that students who report being engaged with a learning task are likely to perform better on that task (Brint, Cantwell & Hannerman, 2008;Carini, Kuh & Klein, 2006;Ewell, 2002), emphasizing the importance of assigning engaging work.…”
Section: Discussionsupporting
confidence: 74%
“…The educational literature indicates that student engagement is generally recognized as one of the better predictors of learning (Brint, Cantwell & Hannerman, 2008;Carini, Kuh & Klein, 2006;Ewell, 2002). Thus, creating classroom conditions that enhance student engagement will lead to increased student learning, which is a primary goal for both students and teachers.…”
Section: Introductionmentioning
confidence: 99%
“…Although much has been published on undergraduate measures of student engagement (Brint, Cantwell & Hannerman, 2008;Zhao & Kuh, 2004;Ewell, 2002), little has been published on graduate student measures of engagement, especially as related to learning tasks assigned for a particular course. In the United States, the National Survey of Student Engagement (NSSE) is notably the most common survey cited for measuring and evaluating undergraduate student engagement factors.…”
Under what conditions are graduate students most likely to learn? How do we, as teachers, best create those conditions? The answer to these questions was the focus of this study whereby 91 masters' students identified learning tasks that were most and least engaging. A model utilizing affective, behavioral and cognitive attributes was developed to measure graduate student engagement in learning tasks. Student survey data demonstrated a direct relationship between perceived value of the learning task, perceived effort put forth in achieving the learning task and perceived student engagement in learning. Multiple regression was used to predict engagement; two attributes, value and effort, predicted 93.2% of the variance in student learning task engagement. Results derived from a repeated measures t-test indicated that students performed significantly better, as measured by grades (p = .003), on learning tasks identified as most engaging when compared to learning tasks identified as least engaging.
“…If students can see the value of the work, they will put forth the effort in completing the learning task (applied expectancy theory). Results of the repeated measures are aligned with the literature indicating that students who report being engaged with a learning task are likely to perform better on that task (Brint, Cantwell & Hannerman, 2008;Carini, Kuh & Klein, 2006;Ewell, 2002), emphasizing the importance of assigning engaging work.…”
Section: Discussionsupporting
confidence: 74%
“…The educational literature indicates that student engagement is generally recognized as one of the better predictors of learning (Brint, Cantwell & Hannerman, 2008;Carini, Kuh & Klein, 2006;Ewell, 2002). Thus, creating classroom conditions that enhance student engagement will lead to increased student learning, which is a primary goal for both students and teachers.…”
Section: Introductionmentioning
confidence: 99%
“…Although much has been published on undergraduate measures of student engagement (Brint, Cantwell & Hannerman, 2008;Zhao & Kuh, 2004;Ewell, 2002), little has been published on graduate student measures of engagement, especially as related to learning tasks assigned for a particular course. In the United States, the National Survey of Student Engagement (NSSE) is notably the most common survey cited for measuring and evaluating undergraduate student engagement factors.…”
Under what conditions are graduate students most likely to learn? How do we, as teachers, best create those conditions? The answer to these questions was the focus of this study whereby 91 masters' students identified learning tasks that were most and least engaging. A model utilizing affective, behavioral and cognitive attributes was developed to measure graduate student engagement in learning tasks. Student survey data demonstrated a direct relationship between perceived value of the learning task, perceived effort put forth in achieving the learning task and perceived student engagement in learning. Multiple regression was used to predict engagement; two attributes, value and effort, predicted 93.2% of the variance in student learning task engagement. Results derived from a repeated measures t-test indicated that students performed significantly better, as measured by grades (p = .003), on learning tasks identified as most engaging when compared to learning tasks identified as least engaging.
“…Large scale studies, which gather data from a range of higher education institutions, are performed annually in both the USA [The National Survey of Student Engagement (NSSE)] and Australia [Australian Survey of Student Engagement (AUSSE)]. However, as noticeable variation between disciplines, countries and universities has been reported [7,8], it is difficult to make generalizations; hence, there is a need to study specific aspects of engagement and individual cohorts of students.…”
Academic staff at universities have become concerned about the decrease in student attendance at lectures and the implication of this on student achievement and learning. Few studies have measured actual lecture attendance in a coherent or comprehensive way. The aim of this study was to measure actual lecture attendance of students over two year levels enrolled in two separate science disciplines, biochemistry and pharmacology. The study further sought to determine the factors that influence lecture attendance. Attendance at lectures in four units of study was monitored over a 12-week semester. Attendance at lectures decreased over the semester and was lower at early morning lectures (8 A.M.; 9 A.M.). A questionnaire surveying students about their preparation for lectures, their compensation for missed lectures and the factors influencing their nonattendance was administered at the end of the semester. Students reported that the major factors influencing their attendance at lectures related to timetable issues and the quality of lecturing. If students missed lectures, the majority read the lecture notes and listened to the online recordings. The availability of online recordings of lectures was not a major influence on attendance at lectures. In three of the four units studied there was no correlation between self-reported lecture attendance and exam performance. The results of the study indicate that universities should dedicate more resources to timetabling and to supporting staff to improve the quality of their lectures.
“…This ideology has been reflected in postgraduate Medical training whereby many training bodies have introduced Mini Case Based Discussion (Mini-Cx) and Directly Observed Practical Skill (DOPS) to their routine evaluations, in a bid to reflect the complexity of real life medical scenarios. This practice represents a welcomed shift from the traditional approach to assessment and learning to the ideals of critical thinking and autonomy in medical education (Brint S, Cantwell AM and Hanneman RA, 2008). …”
Within the arena of medical education, it is generally acknowledged that assessment drives learning. Assessment is one of the most significant influences on a student's experience of higher education and improving assessment has a huge impact on the quality of learning (Liu, N. and Carless, D, 2006). Ideally we want to enhance student's capacity for learning and engagement with the curriculum (ACGME Outcome Project, 2000). However, this doesn't always happen as it is heavily dependent on the form of assessment used and whether or not timely comprehensive feedback is given. This paper focuses on the challenges associated with assessment in medical education and looks at the current trends. Well-designed formative assessment can focus students on effective learning and divert them away from summative assessment, which focuses attention on grades and reproductive thinking (Liu, N. and Carless, D, 2006). Whether one decides to utilise summative or formative assessment methods, both methods of assessment are useful when applied in the correct setting and at an appropriate stage of learning.It is apparent that assessment is the gatekeeper of higher learning and we need to embrace new methods of assessment in order to meet the challenges associated with 'Generation Y'. Novel assessment methods such as self and peer assessment are growing in popularity. Students who participate in these forms of assessment may initially feel that it is challenging but worthwhile overall, as it helps to develop their critical thinking skills. Incorporating complimentary assessment components could benefit student's learning without sacrificing the integrity of the curriculum.
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