APA Sample Research Paper 2016
Introduction
Conducting research and writing research papers is an important part of academic life. Researchers and students need a standardized set of procedures and guidelines to ensure that their work is consistently communicated to readers. The American Psychological Association Style, or APA Style, is an example of a widely used format for writing research papers and documenting sources. This style has a specific format for citing sources used in an APA research paper, as well as guidelines for text formatting, pagination and more. In this paper we will explore an example of an APA research paper from 2016 to illustrate typical components and structure.
The following is an example of an APA style paper often used as a template or example:
Title: Motivation and Performance among University Students: A Study of Achievement Goals
Abstract: This study examined the relationship between achievement goals and academic motivation and performance among university students. A sample of 120 undergraduate students majoring in psychology completed a revised achievement goal questionnaire and measures of intrinsic and extrinsic motivation, self-efficacy, and exam performance. Data were analyzed using correlational analyses and regression analyses. Results indicated that mastery goals were positively related to intrinsic motivation, self-efficacy, and exam performance, whereas performance-approach goals were positively related to extrinsic motivation. Performance-avoidance goals were negatively related to intrinsic motivation and self-efficacy. Multiple regression analyses indicated that mastery goals predicted exam performance beyond prior achievement and demographics. Theoretical and practical implications are discussed.
Introduction:
Motivation is an essential factor influencing students’ academic performance and achievement. Considerable research has examined factors influencing students’ motivational orientations and achievement goals in school settings. Achievement goal theory distinguishes between two general types of achievement goals: mastery goals and performance goals (Dweck, 1986; Nicholls, 1984). Specifically, mastery goals, sometimes called learning goals, refer to the intention to develop competence by mastering a task, increasing one’s knowledge and skills, or accomplishing something challenging. In contrast, performance goals refer to the intention to demonstrate and validate competence or avoid demonstrating lack of competence relative to others (Elliot & McGregor, 2001). Furthermore, performance goals can be subdivided into performance-approach goals, which involve striving to outperform others, and performance-avoidance goals, which involve avoiding performing poorly relative to others (Elliot & McGregor, 2001). A substantial body of research has demonstrated positive relations between mastery goals and beneficial motivational, cognitive, and behavioral outcomes, such as intrinsic motivation, self-regulated learning, cognitive strategy use, task enjoyment, persistence, and performance (Pintrich, 2000). On the other hand, performance goals have been linked to more mixed or negative outcomes depending on the specific type (Elliot & McGregor, 2001).
Despite extensive investigation of achievement goal theory in school contexts, relatively little research has examined achievement goals and their relations to motivation and performance among university students. The current study aimed to extend previous research by investigating the motivational profiles and academic performance associated with different types of achievement goals among undergraduate university students, while controlling for relevant background variables such as prior achievement. Based on past research, it was predicted that mastery goals would relate positively to intrinsic motivation, self-efficacy, and exam performance, whereas performance-approach goals would relate positively to extrinsic motivation, and performance-avoidance goals would relate negatively to intrinsic motivation and self-efficacy. Furthermore, it was expected that mastery goals would predict exam performance beyond the effects of background variables. Improving understanding of motivation among university students could inform efforts to foster adaptive motivation and achievement.
Method
Participants and Procedure
Participants were 120 undergraduate students (80 females, 40 males) from a large public university enrolled in introductory psychology courses. Their ages ranged from 18 to 22 years (M = 19.35, SD = 1.21). Participants received partial course credit for their involvement. All procedures were approved by the university’s research ethics board. The study consisted of a one-time group session during which participants gave consent and completed a confidential online questionnaire containing all measures. Data were collected between September and November 2016.
Measures
Achievement Goals. Students’ achievement goals were assessed using the revised Achievement Goal Questionnaire (Elliot & Murayama, 2008). The instrument consists of 12 items assessing mastery-approach goals (e.g., “My aim is to completely master the material in this class”), performance-approach goals (e.g., “My goal is to perform better than the other students”), and performance-avoidance goals (e.g., “I just want to avoid doing poorly in this class”). Responses were made on a 5-point Likert scale (1 = not at all true of me, 5 = very true of me). Past research supports the validity and reliability of the instrument (Elliot & Murayama, 2008).
Motivation. Students’ motivation was assessed using scales adapted from the Academic Motivation Scale (Vallerand et al., 1992, 1993). Intrinsic motivation was measured with four items assessing interest and enjoyment of schoolwork (e.g., “Because I experience pleasure and satisfaction while learning new things”). Extrinsic motivation was represented by four items assessing external motivations for academic performance (e.g., “In order to obtain a more prestigious job later on”). Responses were made on a 5-point Likert scale (1 = does not correspond at all, 5 = corresponds exactly). The scales have demonstrated reliability and validity in past research (Guay et al., 2010).
Self-Efficacy. General academic self-efficacy expectations were assessed using four items from a scale by Chemers, Hu, and Garcia (2001; e.g., “I’m certain I can understand the most difficult material presented in the readings for this course”). Responses were indicated on a 5-point Likert scale (1 = not at all true, 5 = very true). The scale has evidenced reliability and validity in previous studies ( Chemers et al., 2001).
Academic Performance. Students self-reported their grades on their last two midterm exams in their introductory psychology course as an objective measure of academic performance. Responses were indicated on a standard academic grade scale (0-100).
Background Variables. Students also reported their age, gender, and high school grade point average (GPA) as control variables that have shown relations to achievement and motivation. High school GPA was measured on a 4-point scale and served as a proxy for prior academic achievement.
Results
Preliminary Analyses
Descriptive statistics and bivariate correlations were computed. Internal consistency reliabilities (Cronbach’s alpha) for all multi-item measures were acceptable and similar to published values: achievement goals (.78-.89), intrinsic motivation (.85), extrinsic motivation (.81), and self-efficacy (.82). Consistent with previous research, mastery goals correlated positively with intrinsic motivation (r = .35), self-efficacy (r = .27), and exam grades (r = .19), whereas performance-avoidance goals correlated negatively with intrinsic motivation (r = -.23) and self-efficacy (r = -.18).
Regression Analyses
Multiple regression analyses were conducted to determine if achievement goals predicted motivation, self-efficacy, and exam grades after controlling for background variables. In step 1, age, gender, and high school GPA were entered as controls. In step 2, the achievement goal variables were entered. Results indicated that after controlling for background variables in step 1:
Mastery goals significantly predicted higher intrinsic motivation, ΔR2 = .12, F(1, 116) = 16.53, p < .001. Performance-approach goals significantly predicted higher extrinsic motivation, ΔR2 = .09, F(1, 116) = 11.64, p = .001. Mastery goals significantly predicted higher self-efficacy, ΔR2 = .07, F(1, 116) = 9.08, p = .003. Mastery goals significantly predicted higher exam grades, ΔR2 = .03, F(1, 116) = 4.01, p = .047. Performance-avoidance goals significantly predicted lower intrinsic motivation, ΔR2 = .05, F(1, 116) = 6.09, p = .015, and lower self-efficacy, ΔR2 = .03, F(1, 116) = 3.67, p = .057. Discussion The present study investigated relations between achievement goals and motivation, self-efficacy, and academic performance among undergraduate university students. Consistent with hypotheses and past research, mastery goals were positively associated with intrinsic motivation, self-efficacy, and exam performance, supporting their beneficial role. Meanwhile, performance-approach goals were positively related to extrinsic motivation as predicted. Performance-avoidance goals were negatively related to intrinsic motivation and self-efficacy, consistent with their maladaptive role. Importantly, mastery goals predicted higher intrinsic motivation, self-efficacy, and exam performance beyond background variables, underscoring their relevance for university student achievement. The findings advance knowledge of achievement goal theory and its applicability to the university context while advancing methodological rigor through control variables. Practically, the results highlight mastery goals as an adaptive motivational orientation fostering success. University initiatives and instructors aiming to promote student achievement could focus on nurturing mastery-oriented thinking and learning environments. Of course, limitations include the self-report, correlational design, so directionality and third variables cannot be determined definitively. Future research could employ longitudinal or experimental methods. Overall,
Andrew Stroud