Journal of Nursing Education

Major Article 

Factors Influencing Nursing Student Self-Assessment in Relation to Instructor Assessment

Salam Hadid, PhD, RN



Self-assessment in nursing education is a ubiquitous tool for developing independent learners and critical thinkers. However, self-assessment may be influenced by both demographic and perceptual factors, making it far more complex than students or instructors realize.


A demographically heterogeneous group of nursing students (N = 322) was asked to evaluate their performance of a standard clinical procedure—the insertion of a needle into a peripheral vein of an arm simulator; their assessments were compared with those of an instructor.


Self-assessment is influenced by gender, age, and faith. When student and instructor assessments were compared, a mismatch was found for gender and faith. In addition, a significant positive correlation was found between evaluation mismatch and self-efficacy.


Results of self-assessment, commonly considered an effective tool for teaching skills in general, and clinical work in particular may be skewed by both demographic and perceptual factors. [J Nurs Educ. 2017;56(2):70–76.]



Self-assessment in nursing education is a ubiquitous tool for developing independent learners and critical thinkers. However, self-assessment may be influenced by both demographic and perceptual factors, making it far more complex than students or instructors realize.


A demographically heterogeneous group of nursing students (N = 322) was asked to evaluate their performance of a standard clinical procedure—the insertion of a needle into a peripheral vein of an arm simulator; their assessments were compared with those of an instructor.


Self-assessment is influenced by gender, age, and faith. When student and instructor assessments were compared, a mismatch was found for gender and faith. In addition, a significant positive correlation was found between evaluation mismatch and self-efficacy.


Results of self-assessment, commonly considered an effective tool for teaching skills in general, and clinical work in particular may be skewed by both demographic and perceptual factors. [J Nurs Educ. 2017;56(2):70–76.]

The need for students to develop as independent learners is both fundamental to academic success in higher education and essential to subsequent professional success. One defining characteristic of independent learners is their ability to self-assess (Cassidy, 2007). Assessment, in general, is a vital aspect of learning and is used to evaluate students' knowledge, understanding of content, ability to conceptualize, and capacity to think critically. An important component of this is self-assessment (Karnilowicz, 2012). The process of developing self-assessment involves providing the student with expected standards of professional behavior, including the capacity to recognize one's own abilities and limitations (Gadburg-Amyot, Woldt, & Siruta-Austin, 2015). Self-assessment has been discussed in health science education and professional practice. Students who prepare for a career in health care need to develop self-assessment skills to determine their level of knowledge and identify knowledge gaps to remain current and safe in practice (Baxter & Norman, 2011; Braend, Gran, Frich, & Lindback, 2010).


Self-assessment is defined as a process by which students monitor and evaluate the quality of their thinking and behavior when learning and identify strategies that improve their understanding and skills (McMillan & Hearn, 2009).

In the field of self-assessment, several issues that revolve around the degree of objectivity, accuracy, and stability of the process are discernable. For example, self-assessment can be affected both by personality and by personal, professional, and cultural biases; hence, the roles that cognitive and affective processes play in self-assessment are not at all clear (Kachigwe, Phillips, & Beling, 2015; Sergeant, 2008).

Congruity is lacking between the self-assessment score and the degree of objective success (Colbert-Getz, Flishman, & Jung, 2013). In a study of medical students, Eva, Cunnington, Reiter, Keane, and Norman (2004) reported low correlations. Similarly, a meta-analysis showed a weak association between self-evaluation and external evaluation (Davis et al., 2006).

Theories of psychology present relations between their concepts and processes and self-assessment. One of these theories is the social cognitive theory of Bandura (1986, 1997). Self-efficacy is a component of social cognitive theory, where behavior, cognition, and environment exist in a reciprocal relationship. The self-perception that one has capabilities to perform a task will heighten the likelihood that the task will be completed successfully (Bandura, 1986).

However, on the basis of reports of associations between self-efficacy beliefs and perceptions of academic personal control and perceived academic proficiency, Cassidy and Eachus (2000) found no association at all with self-assessment skills. Similarly, Bandura (1997) found that students with high self-efficacy interpret the gap between their self-efficacy and actual score as a stimulus to work harder, but students with lower self-efficacy are discouraged and do not complete the task because they feel they cannot do it. In addition, Kennedy, Lawton, and Plumlee (2002) and Karnilowicz (2012) concluded that less capable students significantly overestimated their performance, whereas more capable students underestimated their performance. Gadburg-Amyot, Woldt, and Siruta-Austin, (2015) came to a similar conclusion.

Indeed, researchers have not been able to present unambiguous evidence for a causal relationship between self-assessment and student success, nor have they identified the factors that influence student self-evaluation. In fact, self-assessment may be influenced by a number of factors, making it far more complex than students or instructors realize. This assumption has not been rigorously tested or validated (Motycka, Rose, Ried, & Brazeau, 2010).

Personal characteristics have received considerable attention in studies of self-assessment (Colbert-Getz et al., 2013). However, most examined the effect of gender on performance and not on self-assessment. For example, some studies have found that female students underpredict and male students overpredict their performance (Blanch-Hartigan, 2011; Coutts & Rogers, 1999; Langan et al., 2008; Mittelberg & Lev-Ari, 1999; Tariq & Durrani, 2012).

In general, students are capable of reasonably and accurately assessing their own performance relative to tutor assessment, although higher achieving students tend to underestimate their abilities relative to tutor assessment, and lower achieving students tend to overestimate them (Boud & Falchikov, 1989; Karnilowicz, 2012; Kruger & Dunning, 1999). With regard to the assessor, different characteristics of the evaluator are associated with overassessment, underassessment, or accurate assessment (Motycka et al., 2010). There may even be virtually no difference (Cassidy, 2007).

A further issue revolves around the relative validity and accuracy between instructor and student assessments. A deeper understanding of the causes and consequences of overestimation and underestimation is impossible without measuring and reporting the direction of inaccuracy. The least accurate fit is found among lower skilled students or those with exaggerated self-confidence (Davis et al., 2006; Kuncel, Crade, & Thomas, 2005). A study of the link between self-efficacy and success showed that students with high self-efficacy and higher aspirations invested more time in their studies and were more highly evaluated than students with low self-efficacy and low expectations (Bassi, Steca, Fave, & Caprara, 2007).

Several questions can be raised. First, what factors influence student self-assessment? Second, is there a match or mismatch between a student's self-assessment and his or her performance as measured by an instructor; and if so, what are the controlling factors?

The current study examines the factors influencing student evaluation and the way it is conducted and will analyze the relationship between self-assessment and instructor assessment, focusing on the following two sets of variables:

  • Demographic. Gender, age, and religious affiliation (i.e., Jewish, Muslim, Christian, or Druse).
  • Perceptual. The first perceptual factor is the degree of self-efficacy, defined as the belief of the individual in his or her ability to achieve a goal and to successfully perform a particular behavior. Self-efficacy does not refer to an individual's actual skills and talents but rather to his or her perceived ability to perform by means of those same skills. This does not mean that one can achieve goals purely through self-esteem and not through real ability. What is needed is a good fit between belief in one's abilities on the one hand, and one's knowledge and skills on the other (Pajares, 1966).

The second perceptual factor is motivation, and a number of approaches have addressed motivation and its influence on behavior and task fulfilment. One such approach is the expectancy-value theory, which holds that an individual is motivated by his or her concept of the value and the probability of occurrence of a particular objective. The more positive and achievable the value, the greater the likelihood that the individual will strive to achieve it; the more highly valued the expected outcome, the stronger the motivation to perform the task (Atkinson, 1964).

In this study, the authors define motivation as the extent to which the participant attributes importance to the task and the extent of his or her readiness to invest in successful task performance. It is assumed that the higher the importance of the task, the greater the motivation; this assumption is also consistent with the expectancy-value theory, when the importance of the task can be seen as a value. Studies in education have shown that task expectations and task value are the strongest predictors of task success (Eccles & Wigfield, 2002).



  • Hypothesis 1. There will be a relationship between demographic variables and perceptions about the extent of student self-assessment.

  • Hypothesis 2. There will be a relationship between demographic variables and their perception related to a lack of congruence between student self-assessment and that of the instructor.


This quantitative study is based on data collected from nursing student respondents before, during, and after the performance of a clinical procedure—the insertion of a needle into a peripheral vein of an arm simulator.

The task consists of several stages: the preparatory stage is the preparation of the equipment, placing a tourniquet on the arm, identifying the vein most suitable for needle insertion, and disinfecting the skin. Next is the insertion stage, where the needle is inserted into the vein; it must be verified that the needle is correctly placed. The task is completed by inserting a cannula and closing it with a stopper to prevent blood leakage and fixing the cannula to the skin with an adhesive strip. The technique is taught both theoretically and practically, the latter by employing arm simulators looking much like real arms. Using simulators ensures that conditions are the same for all participants in terms of arm size and vein diameter and neutralizes any emotional response that might occur with a living patient (Berman & Snyder, 2012). The data were collected only from written responses, and no think-aloud protocols were used. Because the authors did not want experience to influence self-efficacy, preassessment practice time was not provided. In fact, students who had prior experience of venipuncture were excluded from the cohort.


The participants included 322 nursing students (95 men and 227 women), with a mean age of 26.4 years (SD = 7.65). The participants were from different religions, comprising 134 Jewish, 134 Muslim, 39 Christian, and 15 Druse nursing students. They were selected from the nursing schools of Zefat Academic College, Rebecca Ziv Hospital in Zefat, and Nazareth Hospital. All students were enrolled in regular fundamentals of nursing programs. Those at Zefat Academic College were enrolled in a 4-year baccalaureate program; those from Rebecca Ziv and Nazareth hospitals were enrolled in a 3-year diploma program.


The structured questionnaire was developed by the researcher for this study. One question examined the participant's perception of the degree of difficulty of the procedure on a Likert scale, ranging from 1 = very easy to 6 = very complex.

Another issue involved the degree of-self efficacy in performing the task. Four questions were addressed to the question of the degree of participant confidence in performing the different steps of venipuncture. A Likert scale was used, ranging from 1 = extremely unconfident of doing the procedure to 6 = extremely confident of doing the procedure. Cronbach's alpha for the four questions was .97. A further component of self-efficacy was examined with the question, “To what extent do you think you will succeed in inserting a needle into a peripheral vein?” with answers on a Likert scale ranging from 1 = not at all to 6 = very much. General self-efficacy was calculated by averaging the outcomes for degree of confidence in ability to perform the task and the estimated degree of success.

Participant motivation to perform the task was measured by examining participants' perception of the importance of successful performance. The question was, “How important is it for you to carry out the four steps of the procedure to the best of your ability?” The Likert scale ranged from 1 = not at all important to 6 = extremely important. Cronbach's alpha for this question was .96. General motivation was calculated by averaging the outcomes for the importance of motivation and degree of readiness to invest.

With regard to successful performance as evaluated by the instructors, two instructors carried out in situ observations of the participants separately and without intervening. Afterward, the instructors scored performances according to a structured questionnaire. It contained nine items describing the stages of venipuncture as described above and elsewhere (Berman & Snyder, 2012). Scoring was on a Likert scale ranging from 10 = extremely well executed to 1 = not executed at all. Cronbach's alpha for the questionnaire as filled out by the instructor who acted as tester was .89, and for the instructor who acted as inspector was .90. Reliability between the evaluators was significantly correlated (r = .90, p < .01). The measure of evaluation by instructor was calculated as the average of the evaluation of both instructors.

With regard to successful performance as evaluated by the students, evaluation was performed by the students' self-reported level of success in performing the task. The questionnaire contained the same nine items that were presented to the instructors. Cronbach's alpha for this self-assessment was .89.

Data Analysis

Demographic information was gathered through a questionnaire that included information on age, gender, and religion. Ethical considerations were met by the study being approved by the ethics committee of the University of Haifa. The data was analyzed using SPSS® version 20 software.


The study purpose was to examine the relationship between demographic and perceptual variables and their influence on self-evaluation and the difference between student and instructor assessment of performing a clinical task.

A t test was performed to assess whether a gender difference existed for self-assessment. Men (M = 8.89, SD = 1.23) and women (M = 8.82, SD = 1.25) did not differ significantly, t(.318) = .02, p >.05. However, it appears that age does affect students' self-assessment: Pearson's r test yielded a significant negative correlation between age and degree of self-assessment, r(322) = .22, p < .001. That is, the older the student, the lower the score that the student assigns to his or her own performance.

Students of different faiths evaluated themselves differently. By ANOVA, a strong main effect of religious affiliation was found, F(3, 318) = 5.88, p < .001. The highest level of self-assessment was for Druse students (M = 9.58, SD = .49). The next highest was for Muslim students (M = 9.42, SD = .42), whereas Jewish students gave themselves the lowest self-assessment (M = 8.85, SD = 1.13). However, no significant effect of gender was found related to religious affiliation.

The relationship between the perceptual variables and student self-assessment was also tested. The degree of importance of the task was positively correlated with self-assessment, r(322) = .71, p < .001, as was willingness to invest with self-assessment, r(322) = .14, p < .001. Similar positive correlations were found between self-efficacy and self-assessment, r(322) = .21, p < .05 and motivation and overall self-assessment, r(322) = 16, p < .001. No correlation was found between task complexity and student self-assessment.

A regression analysis was conducted to test the contribution of each variable to overall self-assessment of student task performance (Table 1).

Effects of Independent Variables on the Dependent Variable of Degree of Students' Self-Assessment of Inserting a Needle Into a Peripheral Vein

Table 1:

Effects of Independent Variables on the Dependent Variable of Degree of Students' Self-Assessment of Inserting a Needle Into a Peripheral Vein

The regression analysis (Table 1) shows that age contributes significantly to the explanation of self-assessment, as does self-efficacy. In contrast, Table 1 indicates that motivation does not contribute uniquely to explaining the degree of the students' self-assessment, nor is there an effect of gender in the relationship between self-efficacy and self-assessment.

We also examined the effect of these variables on a mismatch. A mismatch between the two evaluations was defined as the difference between the score given by the instructor and that given by the student. Score variability (a large difference) was interpreted as the student allocating to himself or herself a score higher than that given by the instructor, whereas score congruity (a small difference) showed a match between the two scores. A negative difference indicated a higher score given by the instructor than by the student.

The degree of mismatch ranged between −4 and 4.94 (M = .7, SD = 1.35). The main effect of mismatch was significant, F(3,318) = 87.84, p < .001. However, when the difference in the degree of mismatch was tested between men and women, it was found that men (M = .72, SD = 1.4) did not differ significantly from women (M = .70, SD = 1.3), t[318] = .11, p = not significant). Similarly, student age does not affect the degree of mismatch. By Pearson's r, there was a negative and nonsignificant correlation between age and mismatch in evaluation, r(322) = .05 (p = not significant).

However, a significant main effect of mismatch was found between student and instructor evaluation for religious affiliation, F(3, 318) = 3.29, p < .05, with the strongest mismatch being for the Druse affiliation (M = 1.11, SD = .85), showing that this group yielded the highest positive mismatch between their own and the instructor score. The lowest positive mismatch was found for the Christian affiliation (M = .44, SD = 1.62).

The authors also found a significant mismatch effect for men and women by religious affiliation, F(3,318) = 5.82, p ⩽ .01. The highest positive mismatch was found for male Christian students (a difference of 1.48, SD = 1.32,) and the lowest for male Jewish students (a difference of = .45, SD = 1.32). A further interesting finding was the mismatch between male and female Christian students. That is, male Christian students evaluated their performance more highly than did the instructor (a difference of 1.48, SD = 1.32), whereas Christian female students evaluated themselves lower (a difference of −1.48, SD = 1.48).

The influence of perceptual variables on evaluation mismatch was examined. Although a significant positive correlation was found between evaluation mismatch and self-efficacy, r(322) = .14, p < .05, positive correlations were not found for task importance, willingness to invest, and motivation.

To test the effect of each independent variable on the degree of evaluation mismatch, a regression analysis was performed in stages. The demographic variables were the first stage, the perceptual were the second, and the interaction between them was the third. All three stages yielded significant regressions. Table 2 shows significant effects only.

Regression Analysis Results Showing Effects of Demographic and Perceptual Variables on Self-Assessment Mismatch, Where Significant

Table 2:

Regression Analysis Results Showing Effects of Demographic and Perceptual Variables on Self-Assessment Mismatch, Where Significant

Table 2 shows that both belonging to the Muslim religion and degree of self-efficacy affect the degree of mismatch. The contribution of self-efficacy in determining the degree of mismatch was observed to a high degree among Jewish students and became negative among Druze male students.


The current study examined the effect on self-evaluation of gender, as discussed for example by Colbert-Getz (2013). No significant effects of gender were found related to self-evaluation, an outcome reported by Haist, Wilson, Elam, Blue, and Fosson (2000). However, other studies have found that gender does affect self-evaluation (Blanch-Hartigan, 2011; Coutts & Rogers, 1999; Linda, Rekkas, Bui, Beierile, & Copeland, 2002; Tariq & Durrani, 2012). It should be noted that when the instrument for self-assessment and objective assessment were the same, gender differences were not observed (Motycka et al., 2010). In the current study, students and assessors used the same tool.

Unlike gender, age does have an effect on self-evaluation, with older students scoring themselves lower than younger ones in the task. Most studies do not consider age as a factor affecting the accuracy of self-assessment. One study reported that older women performed better during clinical skills examinations than younger women or men (Haist, Wilson, Elam, Blue, & Fasson, 2000). In the current study, most students were in age 20 to 29 years, which is probably why there was no effect of age on self-assessment.

The current study found that self-evaluation differences exist depending on religion. Druse students gave themselves the highest self-assessment scores, followed by Muslim students and, with the lowest scores, Jewish students. No gender differences were found for religious affiliation. In the literature, little evidence exists for the influence of religion on self-assessment. When the main effect is that of gender, women in the Arab sector score themselves more highly than men (Seginer, 2005; Seginer & Mahajna, 2012).

In the current study, the four perceptual variables of self-efficacy, task importance, readiness to invest, and degree of motivation were significantly correlated with self-assessment. Self-efficacy affects self-assessment, supporting Bandura's theory (1997). As Bandura (1986) stated, students who believe they can perform a certain task usually do not experience negative thoughts about their ability to perform it successfully. Supporting this line of thought is a study by Papinczak, Young, Groves, and Haynes (2007) conducted among medical students.

In contrast, some studies have shown that self-efficacy reduces the degree of self-evaluation (Boud & Falchikov, 1989; Kennedy et al., 2002; Lew, Alwis, & Schmidt, 2010). Self-efficacy certainly plays an important part in determining the degree of self-assessment, but the direction varies; some show that it is heightened, and some, lowered (Cassidy & Eachus, 2000). Another question arising from this study is the extent to which demographic and perceptual variables affect the degree of mismatch or the gap between self-assessment and instructor assessment of a task. This study has shown that there is a mismatch. The significant differences reflect similar results obtained by Colbert-Getz, Flishman, and Jung (2013) and Kim, Choi, Lee, Hong, and Cho (2011). Papinczak, Young, Groves, and Haynes (2007) found that medical students gave themselves lower scores than did the instructor, whereas other studies found goodness-of-fit between the two sets of scores (Cassidy, 2007; Karnilowicz, 2012).

One explanation of the difference between student and teacher assessment is that students interpret assessment criteria differently than their teachers; for example, focusing on superficial features of the performance (Ross, 2006).

In addition, after differences were found between student self-assessment and instructor assessment, the authors wanted to understand the reasons. No differences were found for gender and age to account for the mismatch. In contrast, Papinczak, Young, Groves, and Haynes (2007) found that instructors evaluated older men more highly, and Langan et al. (2008) found that women students evaluated themselves less highly than their instructors, who tended to evaluate male students more highly.

The factor that indicated variance in the mismatch was religious affiliation. The mismatch was largest for the Druse affiliation group followed by the Muslim group. The biggest similarity (i.e., the lowest positive mismatch) was found for the Christian and Jewish groups.

Differences stemming from religious affiliation or culture are not often reported. Researchers have noted that the lack of variation in agreement scores across different characteristics undermines certain results yet aligns with others (Boud & Flachikov, 1989; Lew, Alwis, & Schmidt 2010).

A further interesting finding was a difference in mismatch between Christian male and female participants: males evaluated themselves more highly (i.e., a positive mismatch) but women evaluated themselves less highly (i.e., a negative mismatch) . For all religious groups apart from the Christian affiliation, women gave themselves more positive evaluations. This finding supports other studies finding that Arab women have higher self-assessment than Arab men (Seginer, 2009; Seginer & Mahajna, 2012). However, the opposite effect was reported by Coutts and Rogers (1999), who found that Arab women score their performance lower than do men, compared with an objective assessment.

For the question of the effect of perceptual variables on the degree of mismatch, only self-efficacy was significantly correlated. That is, the higher the student's self-efficacy, the larger the mismatch. These findings reflect those in other studies (Bassi, Steca, Fave, & Caprara, 2007; Karnilowicz, 2012). However, the opposite effect has been also been reported (Braenden, Gran, Frich, & Lindbeack, 2010).

The degree of student self-efficacy has a unique contribution in explaining the high degree of observed mismatch. High self-efficacy is a desirable quality, for as Bandura (1997) noted, students with high self-efficacy interpret the gap between their achievements and their actual results as a stimulus to try harder, in contrast to students with low self-efficacy, who are tired by the effort and decide not to complete the task because they feel they cannot.

In line with other studies, the current study has shown that self-assessment is not an accurate measure. The process currently used to undertake professional development and evaluate competence may need to focus more on external assessment (Davis et al., 2006). The emphasis on self-assessment in nursing may require serious reconsideration in that it is not an effective method to determine an individual's own strengths and weaknesses in the clinical setting (Baxter & Norman, 2011).

Nevertheless, in a review of 63 studies, Dochay, Segers, and Sluijsmans (1999) concluded that self-assessment improves performance and quality of student learning, leads to more reflection on one's own work, a higher standard of the responsibility of outcomes for one's learning, and increased understanding of problem solving. However, it is clear from this study's results that different studies yield different outcomes. Some researchers agree that self-assessment skills remain underdeveloped during the educational process. Although self-assessment is recognized as integral to the development of health professionals, self-assessment skills are rarely taught, and the ability to self-assess is seldom tested (Gadburg-Amyot, Woldt, & Siruta-Austin, 2015). In addition, a recent study (Jackson, 2014) found a pronounced disparity between the understanding of the dimensions of, and influences on, self-assessment. Therefore, a need exists to examine the issue in other areas. To make self-assessment more useful, defining the criteria that students use to assess their work will improve the reliability and validity of assessment, as will teaching students how to apply the criteria and giving them feedback on their self-assessment (Ross, 2006).

Because the literature does not support a unified approach to factors (i.e., demographic and perceptual) influencing self-assessment and mismatch, more studies need to be conducted to better understand student self-assessment, its relation to tutor assessment and the factors that affect them. The paucity of findings in this area and the diversity of students in terms of cultural affiliations support the need for studying larger groups from diverse cultures to arrive at more solid conclusions.


  • Atkinson, J.W. (1964). An introduction to motivation. Princeton, NJ: Van Nostard.
  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
  • Bandura, A. (1997). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215. doi:10.1037/0033-295X.84.2.191 [CrossRef]
  • Bassi, M., Steca, P., Fave, A. & Capara, G. (2007). Academic self-efficacy beliefs and quality of experience in learning. Journal of Youth Adolescence, 36, 301–312. doi:10.1007/s10964-006-9069-y [CrossRef]
  • Baxter, P. & Norman, G. (2011). Self-assessment or self-deception? A lack of association between nursing student's self-assessment and performance. Journal of Advanced Nursing, 67, 2406–2413. doi:10.1111/j.1365-2648.2011.05658.x [CrossRef]
  • Berman, A. & Snyder, S. (2012). Kozier & Erb's fundamentals of nursing: Concepts, process and practice (9th ed.). Upper Saddle River, NJ: Pearson.
  • Blanch-Hartigan, D. (2011). Medical students' self-assessment on performance: Result from three meta-analysis. Patient Education and Counseling, 84, 3–9. doi:10.1016/j.pec.2010.06.037 [CrossRef]
  • Boud, D. & Falchikov, N. (1989). Quantitative studies of student self-assessment in higher education: A critical analysis of findings. Higher Education, 18, 529–549. doi:10.1007/BF00138746 [CrossRef]
  • Braden, A., Gran, S., Frich, J. & Lindbeak, M. (2010). Medical students' clinical performance in general practice—Triangulating assessments from patients, teachers and students. Medical Teacher, 31, 333–339.
  • Cassidy, S. (2007). Assessing “inexperienced” students' ability to self-assess: Exploring links with learning style and academic personal control. Assessment & Evaluation in Higher Education, 32, 313–330. doi:10.1080/02602930600896704 [CrossRef]
  • Cassidy, S. & Eachus, P. (2000). Learning style, academic belief system, self-report student proficiency and academic achievement in higher education, Educational Psychology, 20, 307–322. doi:10.1080/713663740 [CrossRef]
  • Colbert-Getz, J., Flishman, C. & Jung, J. (2013). How do gender and anxiety affect students' self-assessment and actual performance on a high-stakes clinical skills examination?Academic Medicine, 88, 44–48. doi:10.1097/ACM.0b013e318276bcc4 [CrossRef]
  • Coutts, L. & Rogers, J. (1999). Predictors of student self-assessment accuracy during a clinical performance exam: Comparisons between over-estimators and under-estimators of SP-evaluated performance. Academic Medicine, 74(10 Suppl.), S128–S130. doi:10.1097/00001888-199910000-00062 [CrossRef]
  • Davis, D.A., Mazmanian, P.E., Fodis, M., Harrison, V., Thorpe, K.E. & Perrier, L. (2006). Accuracy of physician self-assessment compared with observed measures of competence: A systematic review. JAMA, 296, 1094–1102. doi:10.1001/jama.296.9.1094 [CrossRef]
  • Dochay, F., Segers, M. & Sluijsmans, D. (1999). The use of self-peer and co-assessment in higher education: A review. Studies in Higher Education, 24, 331–350. doi:10.1080/03075079912331379935 [CrossRef]
  • Eccles, J. & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132. doi:10.1146/annurev.psych.53.100901.135153 [CrossRef]
  • Eva, K.W., Cunnington, J.P., Reiter, H.I., Keane, D.R. & Norman, G.R. (2004). How can I know what I don't know? Poor self-assessment in a well-defined domain. Advances in Health Sciences Education, 9, 211–224. doi:10.1023/B:AHSE.0000038209.65714.d4 [CrossRef]
  • Gadburg-Amyot, C., Woldt, J. & Siruta-Austin, K. (2015). Self-assessment: A review of the literature and pedagogical strategies for its promotion in dental education. The Journal of Dental Education, 89, 357–364.
  • Haist, S.A., Wilson, J.F., Elam, C.L., Blue, A.V. & Fosson, S.E. (2000). The effect of gender and age on medical school performance: An important interaction. Advanced Health Science Education Theory Practice, 5, 197–205. doi:10.1023/A:1009829611335 [CrossRef]
  • Jackson, D. (2014). Self-assessment of employability skill outcomes among undergraduates and alignment with academic ratings. Assessment & Evaluation in Higher Education, 39, 53–72. doi:10.1080/02602938.2013.792107 [CrossRef]
  • Kachigwe, A., Phillips, B. & Beling, J. (2015). Videotaping practical examination in physical therapist education: Does it foster student performance, self-assessment, professionalism and improve instructor grading?Journal of Physical Therapy Education, 29, 25–33.
  • Karnilowicz, W. (2012). A comparison of self-assessment and tutor assessment of undergraduate psychology students. Social Behavior and Personality, 40, 591–604. doi:10.2224/sbp.2012.40.4.591 [CrossRef]
  • Kennedy, E.J., Lawton, L. & Plumlee, E.L. (2002). Blissful ignorance: The problem of unrecognized incompetence and academic performance. Journal of Marketing Education, 24, 243–252. doi:10.1177/0273475302238047 [CrossRef]
  • Kim, S.J., Choi, S.H., Lee, S.W., Hong, Y.S. & Cho, H. (2011). The analysis of self and tutor assessment in the skill of basic life support (BLS) and endotracheal intubation: Focused on the discrepancy in assessment. Resuscitation, 82, 743–748. doi:10.1016/j.resuscitation.2011.01.031 [CrossRef]
  • Kruger, J. & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessment. American Psychological Association, 77, 1121–1134.
  • Kuncel, N.R., Crade, M. & Thomas, L.L. (2005). The validity of self-reported grade point averages, class ranks, and test scores: A meta-analysis. Review of Educational Research, 75, 63–82. doi:10.3102/00346543075001063 [CrossRef]
  • Langan, M., Shuker, D., Cullen, R., Penney, D., Preziosi, R. & Wheater, P. (2008). Relationship between student characteristics and self-, peer and tutor evaluation of oral presentation. Assessment & Evaluation in Higher Education, 33, 179–190. doi:10.1080/02602930701292498 [CrossRef]
  • Lew, M., Alwis, W. & Schmidt, H. (2010). Accuracy of students' self-assessment and their beliefs about its utility. Assessment and Evaluation in Higher Education, 35, 135–156. doi:10.1080/02602930802687737 [CrossRef]
  • Linda, D.S., Rekkas, S., Bui, V., Beierile, E. & Copeland, E.M. (2002). Competency-based student self-assessment on a surgery rotation. Journal of Surgery Research, 105, 31–34. doi:10.1006/jsre.2002.6442 [CrossRef]
  • McMillan, J. & Hearn, J. (2009). Student self-assessment. The key to stronger student motivation and higher achievement. Educational Horizons, 87, 40–49.
  • Mittelberg, D. & Lev-Ari, L. (1999). Confidence in mathematics and its consequences: Gender differences among Israeli Jewish and Arab youth. Gender and Education, 11, 75–92. doi:10.1080/09540259920771 [CrossRef]
  • Motycka, C., Rose, R., Ried, L.D. & Brazeau, G. (2010). Self-assessment in pharmacy and health sciences education and professional practice. American Journal of Pharmaceutical Education, 74(5), 1–7. doi:10.5688/aj740585 [CrossRef]
  • Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66, 534–578. doi:10.3102/00346543066004543 [CrossRef]
  • Papinczak, T., Young, L., Groves, M. & Haynes, M. (2007). An analysis of peer, self, and tutor assessment in problem-based learning tutorials. Medical Teacher, 29, 122–129. doi:10.1080/01421590701294323 [CrossRef]
  • Ross, J. (2006). The reliability, validity and utility of self-assessment. Practical Assessment Research and Evaluation, 11(10), 1–13.
  • Seginer, R. (2005). Adolescent future orientation: Intergenerational transmission and intertwining tactics in culture and family settings. In Friedelmeier, W., Pradeeop, C. & Schwartz, B. (Eds.), Culture and human development: The importance of cross-cultural research for the social sciences (pp. 231–251). Hove, England: Psychology Press/Erlbaum (UK).
  • Seginer, R. & Mahajna, S. (2012). With God's help: The future orientation of Israeli Palestinian girls growing up Muslim. In Trommsdorf, G. & Chen, X. (Eds.), Values, religion, and culture in adolescent development. New York, NY: Cambridge University Press.
  • Sergeant, J. (2008). Toward common understanding of self-assessment. Foundation of Continuing Education, 28(1), 1–4.
  • Tariq, V. & Durrani, N. (2012). Factors influencing undergraduates' self-evaluation of numerical competence. International Journal of Mathematical Education in Science and Technology, 43, 337–356. doi:10.1080/0020739X.2011.618552 [CrossRef]

Effects of Independent Variables on the Dependent Variable of Degree of Students' Self-Assessment of Inserting a Needle Into a Peripheral Vein

Independent VariableDependent Variable: Degree of Students' Self-Assessment

Task importance.
Willingness to invest.
General motivation.

Regression Analysis Results Showing Effects of Demographic and Perceptual Variables on Self-Assessment Mismatch, Where Significant

Independent VariableDependent Variable: Mismatch Between Student and Instructor Evaluation

First stage.03*
  Muslim.43.16. 162.62*
Second stage.05*
  Degree of self-efficacy.*
Third stagea.15*
  Interaction: Self-efficacy × Jewish.*
  Interaction: Self-efficacy × Druse−1.58.54−.31−2.91*

Dr. Hadid is Lecturer, Department of Nursing, Zefat Academic College, Upper Galilee, Israel.

The author has disclosed no potential conflicts of interest, financial or otherwise.

Address correspondence to Salam Hadid, PhD, RN, Lecturer, Department of Nursing, Zefat Academic College, 11 Jerusalem Street, P.O.B. 160, Zefat, Israel, 13206; e-mail:

Received: July 10, 2016
Accepted: September 27, 2016


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