Creative Education
2012. Vol.3, Special Issue, 755-760
Published Online October 2012 in SciRes (http://www.SciRP.org/journal/ce) http://dx.doi.org/10.4236/ce.2012.326113
Evaluation of Innovative Teaching Approaches: The Moderating
Effect of Student Prior Experience
Bruce Byrne, Richard Guy
School of Medical Sciences, RMIT University, Melbourne, Australia
Received August 30th, 2012; revised September 30th, 2012; accepted October 13th, 2012
The success of creative or innovative teaching approaches is often measured by student perceptual ratings
of the learning environment or by academic outcomes. This paper examines student perceptions of a
novel human physiology laboratory format and the effect of prior experience on these perceptions. The
same undergraduate human physiology course, taught at second year level, was taken by students who
had previously completed a semester of human physiology (“continuing” students) and by those taking it
for the first time (“new” students). The “continuing” students were significantly more positive about the
novel format compared to the previous format. The class as a whole (“continuing” plus “new”) also gave
a strong positive rating of the novel format. However a comparison between the “continuing” and the
“new” students showed that the latter were significantly more positive in their perception of the laboratory
in all areas apart from active participation. A correlational analysis indicated strong inter-rater links for
the “continuing” students but weak or non-significant inter-rater correlations for the “new” students. The
study suggests that, given the diversity of student backgrounds and prior experience in a given class, that
perceptual ratings of the learning environment alone may not provide enough support for the effectiveness
of novel teaching interventions.
Keywords: Perception; Prior Experience; Engagement; Motivation; Active Learning; Undergraduate
Students; Confidence
Introduction
The measurement of student perceptions of the learning en-
vironment form an important part of the evaluation of learning
and teaching innovations, the results of which may be used at
course, program and university level (Kulic, 2001; Richardson,
2005). However, it is the students’ perception of the learning
context, rather than the context itself, which influences student
approaches to learning (Diseth, Pallesen, Brunborg, & Larsen,
2010) and final academic outcomes. The results of the current
study suggest that prior experience may affect student percep-
tions of the learning environment and that conclusions based on
ratings alone may not allow conclusions to be reached regarding
the efficacy of interventions. Given the lack of research on the
agreement of student ratings of group level constructs in educa-
tional research (Lüdtke, Trautwein, Kunter, & Baumert, 2006)
the results may have wider implications for the evaluation of
teaching and learning innovations and the conclusions derived at
all levels of the hierarchy.
This paper explores the introduction of a novel approach to
improve students’ human physiology laboratory experiences and
the concurrent student perceptions of the approach. One of the
major experiences undergraduate students have in most sci-
ence-based courses is their involvement in hands-on laboratories.
However, end-of-semester examination results suggested to staff
teaching human physiology at RMIT University that students’
had not fully understood concepts derived from their physiology
laboratory experience. For this reason a novel physiology labo-
ratory approach was developed based on the fact that students’
motivation and deeper learning of concepts is increased with
well-designed laboratory work, (Hoffstein & Lunetta, 1982) and
that students’ understanding is enhanced when they actively
engage in the learning process (Jonassen, 1999; Kearney, 2004;
Land & Hannafin, 2000; Mayer, 2003). We focused on im-
proving students’ engagement with the learning activity by
considering involvement in and engagement with the learning
activities (cognitive engagement) and also behavioral engage-
ment (interest, enjoyment and a sense of belonging) (Fredericks,
Blumenfeld, & Paris, 2004; Harper & Quaye, 2009). Students
who are engaged are intrinsically motivated with self-belief in
their own abilities, have a desire to improve their competency,
need to develop their own learning and to be able to achieve their
goals (Ainley, 2006; Yorke & Knight, 2004; Zepke & Leach,
2010). Self-perceived competence is a key motivator for en-
gagement and when students have confidence in their own
competence this is a strong motivator for ongoing active learning
(Fazey & Fazey, 2001).
The initial purpose of the study was to establish, by analyzing
student ratings of the learning environment, whether the novel
laboratory format enhanced students’ engagement, active learn-
ing and perceived understanding of key concepts. The impact of
student prior experience on the validity of our approach was
further investigated through inter-rater analysis.
Method
One hundred and two students taking a human physiology
course at RMIT University (40% of the class) were surveyed
using an end of semester questionnaire. The aim of the survey
was to ascertain from the students their responses to the new

B. BYRNE, R. GUY
laboratory format. Students were asked to give their responses
on a range of questions including their active participation in the
laboratories and their confidence in doing the laboratories and to
how well they thought the assessment fairly reflected what they
had done in the laboratories.
Two physiology courses are taught at second year under-
graduate level (one in first semester and the second in second
semester). However, due to program requirements, the second
semester student cohort consists of second year students who
have already completed first semester physiology (“continuing”
students—Biomedical Science, Human Movement and Phar-
maceutical Sciences programs) and first year students (“new”
students—Chiropractic, Osteopathy and Chinese Medicine pro-
grams) taking their first physiology course. The latter “new”
students complete their physiology sequence in the first semester
of second year (in reverse order to the students in the other
programs). Permission was obtained from the RMIT University
Human Ethics Committee (low risk) and students were informed
of the purpose of the survey and given a plain-language state-
ment. No individual student identifiers were used, however
student survey responses were divided into those who had
(“continuing” students) or had not (“new” students) completed a
prior semester of human physiology.
The new laboratory approach had two key components: a
one-hour concept-focused human physiology laboratory and an
immediate follow-up interactive discussion with feedback and
associated assessment (one hour). This replaced the previous
structure of a two-hour more detailed hands-on laboratory
without follow-up discussion, feedback or immediate assess-
ment.
The academic in charge of each section of the course identi-
fied material that was best suited to a short focused hands-on
laboratory that would help students in understanding key con-
cepts. Once students completed the hands-on component of the
laboratory they took part in a one-hour interactive group session
invigilated by a tutor. During this session problems and ques-
tions associated with the laboratory were discussed and the
material covered in the laboratory was integrated into theory.
The assessment task entailed a series of multiple-choice ques-
tions as well as students filling out a section giving their own
reflections. The tutor marked these assessment sheets after each
laboratory and feedback was provided to students in the next
laboratory class.
The first part of the survey consisted of five questions (Table
1) that were only answered by the “continuing” students (Bio-
medical Science, Human Movement and Pharmaceutical Sci-
ence Programs). These questions allowed comparison between
the novel laboratory format and the original laboratory format
taken by these students in the preceding semester. The second
part of the survey was taken by all students (Table 2) (Bio-
medical Science, Chiropractic, Osteopathy, Chinese Medicine,
Human Movement and Pharmaceutical Sciences programs) and
consisted of eight questions designed to gather students’ inter-
pretations about their learning, the format of the laboratory and
the interactive post-laboratory discussion as well as their reflec-
tions on their level of participation, confidence, enjoyment and
satisfaction.
The survey used a five point Likert scale (Strongly agree (5),
Agree (4), Neither Agree nor Disagree (3), Disagree (2),
Strongly Disagree (1)), with a high reliability score (Cronbach’s
alpha = .87) for the survey items (for the items only for the
“continuing” students, α = .95, and items for both “continuing”
Table 1.
Questions given only to the “continuing” students (first part of survey).
Parameter Question
NCon I found the new format gave me more confidence
in learning
NU I found the new format helped me understand
the material better
NC I found that what I was supposed to learn was
clearer than last semester
NE I enjoyed the new laboratory format better
NStr I was more satisfied with the new laboratory
structure than the previous one
Table 2.
Questions given to all students (second part of survey).
Parameter Question
End-laboratory The use of end-lab discussion aided my
learning
Combination
The combination of hands-on and end-lab
discussion helped me to be more involved in
the practical
Active I was an active participant in the end-lab discussion
Assessment The end-lab discussion gave me more confidence
in doing the assessment
Enjoyment I found the laboratory experience enjoyable
Feedback The end-lab discussion gave me good feedback on
my understanding of the concepts of the lab
Fairly The assessment fairly assessed what was covered in
the lab
Satisfaction I was satisfied how the laboratory and assessment
were carried out
and “new” students, α = .81). No student identifier was recorded
on the survey. The survey was administered over a two-week
period during the laboratory sessions. Once the data had been
collated they were analyzed using SPSS©. Initial Pearson cor-
relations were carried out along with tests for homogeneity and
normality, and ANOVA (α = .05).
Results
When comparing the original with the novel laboratory for-
mats (first part of the survey) the “continuing” students were
more satisfied with the new format than their previous one, with
responses for all questions averaging 3.94 (SD = .4) (Agree = 4).
They reported more understanding of the material, were
clearer in what they had to learn, enjoyed the new format better,
and were more satisfied with the new laboratory structure. There
were no significant differences between the responses to any of
these questions. The ratings and inter-rater correlations for the
responses to these questions are presented in Figure 1.
The response of the entire class to the novel format is shown
in Figure 2. An initial survey of all students (“continuing” and
“new” students) showed that the average response was very
positive for all the parameters. However, when an examination
was made of the two distinct groups a different pattern emerged.
The ratings for each question in the second part of the survey are
756

B. BYRNE, R. GUY
Figure 1.
Comparison of correlations (numbers on lines) and
student responses (numbers in shapes) for the ques-
tions only for the “continuing” students comparing
the old and new formats. NCon = New Confidence;
NC = New Clear; NE = New enjoyment; NU = New
Understanding; NStr = New Structure. Significance
of difference is at p < .05*; p < .01**.
shown in Figure 2(a) (“new” students) and (b) (“continuing”
students). The “continuing” students ratings were significantly
less positive than those for the “new” students for enjoyment in
doing the laboratory (“new” students 4.6; “continuing” students
3.8; F (1,101) = 15.74, p < .01). There was also a smaller sig-
nificant difference between the groups for how much the com-
bination of hands-on laboratory and discussion helped them to
be more involved in the laboratory (“new” students 4.7; “con-
tinuing” students 4.2; F (1,101) = 8.12, p < .05); the end-of
laboratory discussion giving them more confidence in doing the
assessment (“new” students 4.5; “continuing” students 4.0; F
(1,101) = 6.38, p < .05); the laboratory assessment fairly as-
sessing what was done in the laboratory (“new” students 4.8;
“continuing” students 4.3; F (1,101) = 10.70, p < .05); and stu-
dents’ satisfaction about how the laboratory and the assessment
were carried out (“new” students 4.5; “continuing” students 4.3;
F (1,101) = 11.97, p < .05). Despite these results there was no
difference between the “new” and “continuing” students re-
ported active participation in the laboratory (“new” students 4.0;
“continuing” students 3.7).
Correlations between the student ratings for each question in
the second part of the survey are shown in Figures 2(a) (“new”
students) and (b) (“continuing” students). The “continuing” stu-
dents had significantly higher correlations between feedback on
concepts from the end-laboratory discussion and the laboratory
assessment fairly assessing what was covered in the laboratory
(“continuing” students r = .72, p < .01; “new” students r = .39,
p < .05). Furthermore the “continuing” students had a signifi-
cantly higher correlation between the end-laboratory discussion
aiding their learning, and their satisfaction about how the labo-
ratory and assessment were carried out (“continuing” stu-
dents r = .45, p < .01; “new” students r = .02, p > .05). The
“continuing” students also had a higher significant correlation
between enjoying the laboratory experience more in relation to
their learning being aided by the end-laboratory discussion
(“continuing” students r = .44, p < .01; “new” students r = .23,
p > .05); between the end-laboratory discussion and the as-
sessment (“continuing” students r = .36, p < .05; “new” stu-
dents r = .07, p > .05); between satisfaction of the laboratory
and assessment, and enjoyment (“continuing” students r = .67,
p < .01; “new” students r = .29, p > .05).
(a)
(b)
Figure 2.
Comparison of correlations (numbers on lines) and stu-
dent responses (numbers in shapes) for both “new” (a)
and “continuing” (b) students. Significant difference for
“new” compared with “continuing” is at p < .05*; p
< .01**; NS = not significant. FB = Feedback; ASS =
assessment; ELD = End-Lab Discussion; COM = Com-
bination of end-lab and hands-on; SAT = Satisfied; LAB =
Enjoyed Lab.
Discussion
Our initial evaluation of the human physiology laboratory
innovation was that it was successful, based on the significant
increase in positive responses from the “continuing” students
when they compared the new with the previous format. In
addition the group response to questions related to the new
format (“new” students plus “continuing” students) was also
very positive. Our initial conclusion from the study was that
students’ motivation and engagement was enhanced by a com-
bination of a simpler concept focused hands on laboratory ses-
sion and a post-laboratory interactive group discussion (active
learning) with associated assessment. An affective component,
enjoyment, was also enhanced resulting in an overall more
positive learning experience than provided by the previous
physiology laboratory format. In a study of a measure of student
course engagement (Handelsman, Briggs, Sullivan, & Towler,
2005) the importance of participation/interaction in relation to
student engagement was demonstrated. This was one of four
engagement factors identified however it was the only one that
was predictive of students’ final exam mark. Active learning
engages students and involves them in doing things and in

B. BYRNE, R. GUY
thinking about what they are doing (Michael, 2006; Prince,
2004).
However, comparison of the sub-groups within the class
demonstrated that for many areas the “new” students had a
significantly greater positive rating of the novel laboratory
format than the “continuing” students. It is possible that the
differences are due to differences in the degree of motivation of
the two groups as student motivation moderates perception of
the learning environment and determines approaches to learn-
ing and outcomes (Biggs, 1985; Ramsden, 1991). Students’
perceptions of the learning environment (in this case workload)
have been found to be a function of individual characteristics,
approaches to and perceptions of the learning context (Kember,
Ng, Tse, Wong, & Pomfret, 1996). Motivation (and satisfaction)
of students within a course may also depend on whether or not
they intend to continue in that area of study. Diseth et al. (2010)
found students, within a first semester psychology course, who
did not plan to continue their psychology studies, were less
satisfied with their quality of education and had a higher level
of surface approach than those who did want to continue.
However, in contrast, students who intended to continue in
aviation were less satisfied with an online aviation physiology
course compared to students who were not going to continue in
aviation (Artino, 2009), even though they reported greater per-
ceptions of task value and greater use of cognitive control
strategies. In this case it was suggested that the lower satisfac-
tion of the “aviators” resulted from the course not meeting their
expectations. It was concluded that subjective perceptions of
the learning environment moderated motivational and beha-
vioral engagement (Artino, 2009).
In general, intrinsic motivation is more likely to be associ-
ated with a deep approach to learning and increased positive
perceptions of the learning environment (Ramsden, 1992). In a
series of studies Deci and Ryan (Deci & Ryan, 2000; Ryan &
Deci, 2000a, 2000b) identified intrinsic motivation, in which
students do something because it is interesting or enjoyable, as
assisting self-determination. With an increase in self-determi-
nation students develop an increase in autonomy in their learn-
ing experience and students are more highly motivated for
skills they value and wish to master. Significant perceptual
differences have been found between students who had or had
not studied science prior to entry into a new integrated anatomy
practical program. Nonscience students were more positive
regarding structure, organization, resources, problem-based
learning and assessment fairness within the new program, pos-
sibly due to their relative lack of understanding and their desire
to succeed (Tedman, Alexander, Massa, & Moses, 2011).
Our study focused on the presage components of the Biggs
(1989) 3P model of teaching and learning i.e. what student prior
experience contributes to the learning situation (prior knowledge,
academic ability, personality etc.) and the characteristics that
define the learning environment itself (e.g. quality of teaching).
It is also important to establish the relationship between learning
environments and students’ affective experiences as the results
support the conclusion that students learn better by not only
becoming active participants in their own learning but also by
enjoying what they are doing. As indicated above affective
components may be related to intrinsic motivation and deep
learning (e.g. enjoyment) or to extrinsic motivation and surface
learning (e.g. unhappiness). Negative affect may develop under
certain circumstances. For example some students develop
negative perceptions of group work (Forrest & Miller, 2003) that
may lead to continuing negative attitudes regarding the effec-
tiveness of small groups in enhancing their learning (Forrest &
Miller, 2003; Hillyard, Gillespie, & Littig, 2010).
The question remains, however, as to whether any of the
factors discussed above, that affect student perception of their
learning environment, provide a reasonable explanation for the
differences that we observed. One possibility is that the “new”
students had a higher level of intrinsic motivation due to their
desire to succeed notwithstanding a relative lack of experience
(as they were first year students). They could also be considered
to be anticipating the fact that they would progress to an addi-
tional semester of physiology whereas the “continuing” students
were completing their second year physiology studies. However,
this seems unlikely as physiology is a core component of the
programs in both groups (i.e. it is important for their further
studies). Another possibility is that the “continuing” students
had developed a negative attitude to physiology as a result of
their prior semester of physiology or as a result of their general
experience of tertiary study. This also seems unlikely as they
preferred the new laboratory format, (compared to the previous
one) and gave an overall positive response. Another option
would be that the “continuing” students had become less intrin-
sically motivated due to a high workload at this stage of their
degree. As discussed above a high workload can result in an
increased surface approach to learning with a concurrent de-
crease in positive perceptions of the learning environment.
However, workload was not measured in the current study.
A final possibility is based on the level of knowledge and
understanding of the learning environment. “What the learner
already knows” (Marton & Booth, 1997) are elements of the
student’s prior experience that they reference in a given learning
situation. In terms of the relationship between the student and the
learning environment (relational perspective) part of the mean-
ing that someone ascribes to learning comes from their under-
standing of the particular setting that they are in (Saljo, 1982). A
number of studies have found that people tend to be overconfi-
dent in their judgments, particularly when those judgments are
difficult to make, for example, students who were less aca-
demically competent tended to overestimate their abilities
(Langendyk, 2006). However, other studies have found that
surface learners provide lower evaluations of their own per-
formance whereas deep learners accurately self-assess (Cassidy,
2007).
Thus it is possible that the “new” students are less able to
“benchmark” their responses to the questionnaire due to relative
inexperience regarding physiology laboratories. They are unable
to make the same comparison made by the “continuing” students
who previously completed a semester of physiology laboratories.
The “new” students may also have more limited general know-
ledge of academic study as they are only in the second semester
of their first year of study. In conclusion the higher ratings pro-
vided by the “new” students may reflect an overestimation re-
lated to their lack of a satisfactory benchmark.
A correlational method was used in an attempt to determine
which of the various explanations discussed above would ex-
plain the discrepancy in ratings of the new laboratory format
between “new” and “continuing” students. The rationale for this
approach was that experienced (“continuing”) students would
demonstrate understanding of the links between the different
aspects of the survey questionnaire at a higher level than that for
the relatively less experienced “new” students. Correlational
analysis has been used to support links between higher-level
758

B. BYRNE, R. GUY
measurements e.g. to determine the relationship between pres-
age, process and product, as in the Biggs 3P model, (Biggs, 1989)
however it is much rarer to find this approach used to examine
links within a class. The “absolute agreement” of students within
a class can be measured. However, Lüdtke et al. (2006) indicate
that very little educational research has been conducted on the
agreement of student ratings of group-level constructs. A study
describing instruments designed for evaluating clinical faculty
by learners found only 9 of 21 relevant studies measured inter-
rater reliability (Beckman, Ghosh, Cook, Erwin, & Mandrekar,
2004). Our data demonstrates a clear difference between the
degree of inter-rater agreement within the “new” student group
and the “continuing” student group. The high level of correlation
between different elements of the survey shown by the latter
group both within their comparison between old and new labo-
ratory formats and within their perception of the new format may
indicate their greater ability to benchmark their answers against
prior experience. On the other hand the lack of correlation be-
tween student ratings within the “new” group may indicate their
lack of experience and lack of reference to appropriate bench-
marks.
If one accepts that the low correlations for inter-rater re-
sponses amongst the “new” students indicates a lack of prior
relevant experience, then their higher ratings of the innovative
physiology laboratory might either reflect a high level of moti-
vation related to their lack of experience and their need to do
well or that they produced an inflated response due to lack of
benchmarks. Conversely the lower positive ratings of the “con-
tinuing” group may provide a more realistic measure of the
innovation given the strong relationships between the student
responses and the more relevant prior experience of these stu-
dents. Although the correlational technique is not the only
method of measuring inter-rater agreement, one is left with the
conclusion that with respect to student perceptual ratings, high-
est is not necessarily the best indicator of innovation success.
When evaluating learning and teaching innovations attention
should be paid to the diversity of the student cohort and the
presence of subgroups and it may be appropriate to investigate
analysis methods other than simply measuring the level of stu-
dent ratings. The same conclusion may also apply when con-
sidering higher-level analysis built on course level feedback.
REFERENCES
Ainley, M. (2006). Connecting with learning: Motivation, affect and
cognition in interest processes. Educational Psychology Review, 18,
391-405. doi:10.1007/s10648-006-9033-0
Artino, A. R. (2009). Online learning: Are subjective perceptions of
instructional context related to academic success? The Internet and
Higher Education, 12, 117-125. doi:10.1016/j.iheduc.2009.07.003
Beckman, T. J., Ghosh, A. K., Cook, D. A., Erwin, P. J., & Mandrekar,
J. N. (2004). How reliable are assessments of clinical teaching? A
review of the published instruments. Journal of General Internal
Medicine, 19, 971-977. doi:10.1111/j.1525-1497.2004.40066.x
Biggs, J. (1985). The role of metalearning in study process. British
Journal of Educational Psychology, 55, 185-212.
doi:10.1111/j.2044-8279.1985.tb02625.x
Biggs, J. B. (1989). Approaches to enhancement of tertiary teaching.
Higher Education Research & Development, 8, 7-25.
doi:10.1080/0729436890080102
Cassidy, S. (2007). Assessing “inexperienced” students’ ability to
self-assess: Exploring links with learning style and academic per-
sonal control. Assessment & Evaluation in Higher Education, 32,
313-330. doi:10.1080/02602930600896704
Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of goal
pursuits: Human needs and the self-determination of behavior.
Psychological Inquiry, 11, 227-268.
doi:10.1207/S15327965PLI1104_01
Diseth, Å., Pallesen, S., Brunborg, G. S., & Larsen, S. (2010).
Academic achievement among first semester undergraduate psy-
chology students: The role of course experience, effort, motives and
learning strategies. Higher Education, 59, 335-352.
doi:10.1007/s10734-009-9251-8
Fazey, D. M. A., & Fazey, J. A. (2001). The potential for autonomy in
learning: Perceptions of competence, motivation and locus of control
in first-year undergraduate students. Studies in Higher Education, 26,
345-361. doi:10.1080/03075070120076309
Forrest, K. D., & Miller, R. L. (2003). Not another group project: Why
good teachers care about bad group experiences. Teaching of
Psychology, 30, 244-246.
Fredericks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School
engagement: Potential of the concept, state of the evidence. Review
of Educational Research, 74, 59-109.
doi:10.3102/00346543074001059
Handelsman, M. H., Briggs, W. L., Sullivan, N., & Towler, A. (2005).
A measure of college student course engagement. The Journal of
Educational Research, 98, 184-191. doi:10.3200/JOER.98.3.184-192
Harper, S. R., & Quaye, S. J. (2009). Beyond sameness, with engage-
ment and outcomes for all. In S. R. Harper, & S. J. Quaye (Eds.),
Student Engagement in Higher Education (pp. 1-15). New York and
London: Routledge.
Hillyard, C., Gillespie, D., & Littig, P. (2010). University students’
attitudes about learning in small groups after frequent participation.
Active Learning in Higher Education , 11, 9-20.
doi:10.1177/1469787409355867
Hoffstein, A., & Lunetta, V. N. (1982). The role of the laboratory in
science teaching. Review of Educational Research, 52, 201-217.
Jonassen, D. (1999). Designing constructivist learning environments. In
C. M. Reigeluth (Ed.), Instructional theories and models (2nd ed., pp.
215-239). Hoboken: Taylor & Francis.
Kearney, M. (2004). Classroom use of multimedia-supported predict-
observe-explain tasks in a social constructivist learning environment.
Research in Science Education, 34, 427-453.
doi:10.1007/s11165-004-8795-y
Kember, D., Ng, S., Tse, H., Wong, E. T. T., & Pomfret, M. (1996). An
examination of the interrelationships between workload, study time,
learning approaches and academic outcomes. Studies in Higher
Education, 21, 347-358. doi:10.1080/03075079612331381261
Kulic, J. (2001). Student ratings: Validity, utility and controversy. New
Directions for Institutional Res e a rch, 109, 9-25. doi:10.1002/ir.1
Land, S., & Hannafin, M. (2000). Student centered learning environ-
ments. In D. H. L. Jonassen, (Ed.), Theoretical foundations of learn-
ing environments. Hoboken: Taylor & Francis.
Langendyk, V. (2006). Not knowing that they do not know: Self-
assessment accuracy of third-year medical students. Medical Educa-
tion, 40, 173-179. doi:10.1111/j.1365-2929.2005.02372.x
Lüdtke, O., Trautwein, U., Kunter, M., & Baumert, J. (2006). Relia-
bility and agreement of student ratings of the classroom environment:
A reanalysis of TIMSS data. Learning Environments Research, 9,
215-230. doi:10.1007/s10984-006-9014-8
Marton, F., & Booth, S. (1997). Learning and awareness. Hoboken, NJ:
Taylor & Francis..
Mayer, R. E. (2003). Theories of learning and their applications to
technology. In H. F. P. O’Neil, (Ed.), Technology applications in
education (pp. 127-157). Hoboken: Taylor & Francis.
Michael, J. (2006). Where’s the evidence that active learning works?
Advances in Physiology Education, 30, 159-167.
doi:10.1152/advan.00053.2006
Prince, M. (2004). Does Active Learning Work? A Review of the
Research. Journal of Engineering Education, 93, 223-231.
Ramsden, P. (1991). A performance indicator of teaching quality in
higher education: The course experience questionnaire. Studies in
Higher Education, 16, 129-150.
doi:10.1080/03075079112331382944
Ramsden, P. (1992). Learning to teach in higher education. London:

B. BYRNE, R. GUY
760
Routledge. doi:10.4324/9780203413937
Richardson, J. T. E. (2005). Instruments for obtaining student feedback:
A review of the literature. Assessment & Evaluation in Higher
Education, 30, 387-415. doi:10.1080/02602930500099193
Ryan, R. M., & Deci, E. L. (2000a). Intrinsic and extrinsic motivations:
Classic definitions and new directions. Contemporary Educational
Psychology, 25, 54-67. doi:10.1006/ceps.1999.1020
Ryan, R. M., & Deci, E. L. (2000b). Self-determination theory and the
facilitation of intrinsic motivation, social development, and well-
being. American Psychologist, 55, 68-78.
doi:10.1037/0003-066X.55.1.68
Saljo, R. (1982). Learning and understanding: A study of differences in
constructing meaning from a text. Goteborg: ACTA Universitatis
Gothoborgensis.
Tedman, R. A., Alexander, H., Massa, H., & Moses, D. (2011). Student
perception of a new integrated anatomy practical program: Does
students’ prior learning make a difference? Clinical Anatomy, 24,
664-670. doi:10.1002/ca.21180
Yorke, M., & Knight, P. (2004). Self-theories: Some implications for
teaching and learning in higher education. Studies in Higher Edu-
cation, 29, 25-37. doi:10.1080/1234567032000164859
Zepke, N., & Leach, L. (2010). Improving student engagement: Ten
proposals for action. Active Learning in Higher Education, 11,
167-177. doi:10.1177/1469787410379680