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DOI: 10.1039/C2RP20004J (Paper) Chem. Educ. Res. Pract., 2012, 13, 237-247

The interplay of students' motivational orientations, their chemistry achievements and their perception of learning within the hands-on approach to visible spectrometry

Mojca Juriševič a, Margareta Vrtačnik b, Marek Kwiatkowski c and Nataša Gros d
aFaculty of Education, University of Ljubljana, Slovenia. E-mail: mojca.jurisevic@pef.uni-lj.si
bFaculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia
cFaculty of Chemistry, University of Gdansk, Poland
dFaculty of Chemistry and Chemical Technology, University of Ljubljana, Slovenia

Received 13th December 2011 , Accepted 16th February 2012

First published on 2nd April 2012

Abstract

The purpose of the study was to determine the relationship between students' motivational orientations and their chemistry achievements and perception of learning within the original case of the hands-on approach to visible spectrometry. A total of 295 students from Polish and Slovenian vocational and technical high schools participated in the study. By applying the k-mean clustering procedure, two distinct clusters of students' motivational orientations were identified based on the SDT theory about autonomous and controlled motivation. Students classified as the good quality motivation group (Cluster II) outperformed students in the low quantity motivation group (Cluster I) in their knowledge gained through the hands-on approach and assessed the hands-on approach more positively with regard to their active participation in learning selected concepts from visible spectrometry. Altogether, the results of the present study confirm previous research findings about the importance of the quality of students’ motivation for learning; the results show that hands-on laboratory work with autonomy-supportive teachers could create a motivating learning environment for students to learn with understanding and to cooperate with each other in academic tasks at a higher level of cognitive complexity. The main implication for teachers in chemistry classes is, therefore, to plan their teaching more systematically and creatively in order to provide students with individualised cognitively and motivationally challenging learning situations (both in terms of content and didactical methods) and to foster learning with understanding even within very abstract and cognitively complex learning tasks.

Introduction

Rapid technological development requires professionals with excellent analytical chemistry skills in order to monitor technological processes and their impact on the environment, as well as to control food safety and people's health. A report of the European Training Foundation (Masson, 2005) reveals that European vocational education is undergoing a crisis. The study additionally indicates that vocational education in new member states, in contrast with EU-15 states, is experiencing a decrease in enrolment rates. Vocational education and training (VET) in these countries is under-funded and is becoming more and more technical and pre-vocational, preparing students for further studies after graduation, and less and less vocational, preparing them for entering the labour market after graduation.

The situation in VET in chemistry-based or chemistry-related disciplines is even less favourable. A report on science education in school (TLRP, 2006) indicates that the great majority of pupils at the pre-vocational level adopt a reluctant attitude towards natural sciences (i.e., consider them difficult, demanding and not very exciting). As a consequence, they seldom recognise disciplines such as chemistry, laboratory medicine and food processing as providing an attractive future career opportunity. This is not necessarily a real lack of predispositions for these areas; it might well be the influence of the prevailing opinion in their environment and within their peer group, in combination with a lack of opportunities for recognising real personal talents and interests.

In response to these problems an international project “Hands-on approach to analytical chemistry for vocational schools” was supported by Leonardo da Vinci Lifelong Learning Programme “Transfer of Innovation”. The project aimed at contributing to the better quality and attractiveness of VET (more specifically vocational schools for food processing, chemistry and laboratory medicine) in chemistry-related and chemistry-based disciplines by implementing small-scale low-cost spectrometers that can be easily upgraded into other analytical instruments (Gros, 2001, 2004). The instrument was used in the present study for the introduction of basic knowledge from visible spectrometry through the hands-on approach.

The purpose of the study and the research questions

The purpose of the study was to determine the relationship between students' motivational orientations, their chemistry achievements and their perception of learning within the hands-on approach to visible spectrometry. More specifically five research questions were set up as follows: (1) What is the relationship between students' motivational orientations and their final chemistry grades from the previous school year?, (2) What is the relationship between students' motivational orientations and their prior knowledge gained through personal experiences with light and colour (experiential knowledge)?, (3) What is the relationship between students' motivational orientations and their knowledge gained through the hands-on approach during working with selected modules from visible spectrometry (hands-on knowledge)?, (4) What is the relationship between students' motivational orientations and their perception of the hands-on approach used?, (5) What is the relationship between students' motivational orientations and the specific knowledge and skills gained throughout working with selected modules?

The hands-on approach in teaching and learning chemistry

Research focusing on theories of knowledge acquisition in the last decades (Posner, 1982; Hewson and Hewson, 1984; Dreyfus et al., 1990; Duschl and Gitomer, 1991; Dykstra et al., 1992; Chinn and Brewer, 1993; Smith et al., 1993; Niaz, 1995) has evoked changes in educational practice. Studies have shown that the traditional textbook and lecture paradigm involving students as passive recipients of facts is not the most effective way to teach (Yager, 1991; Dykstra et al., 1992). By understanding the process of learning, science instruction can evolve into a model in which students become active participants in the development of their own theoretical frameworks. As a practical result of these research efforts a series of student-centred teaching strategies has been introduced in classroom settings, including group discussions, problem-based learning, student-led review sessions, think-pair-share, student-generated examination questions, mini-research proposals or projects, a class research symposium, simulations, case studies, role plays, journal writing, concept mapping, structured learning groups, cooperative learning, collaborative learning, an enquiry-based approach, and a hands-on/minds-on approach to teaching and learning; the last two strategies are especially suitable for learning experimental sciences such as chemistry (Weaver, 1996; Vrtačnik and Gros, 2005). On the basis of extensive meta-analytical study which comprised 119 studies with 1450 relevant findings Cornelius-White (2007) concluded that student-centred approach and positive teacher-student relationships are associated with optimal, holistic learning and are correlated higher with cognitive and especially affective and behavioural outcomes if compared with other educational innovations. However, the level of choice and autonomy of students while learning through student-centred approach depends on how much teacher structure is supplied during the learning process, and whether there is an already existing solution to the problem or question under exploration (Herron, 1971). Flick (1993) defined hands-on science as a philosophy guiding the usage of the different teaching strategies needed to address diversity in classrooms, on the one hand, and as a specific instructional strategy in which students are actively involved in manipulating materials and instruments, on the other.

Results of studies on the effects of thematic, hands-on science teaching and enquiry-based approaches versus the textbook approach are contradictory. In the 1990s, a large number of American elementary schools started teaching science based on hands-on enquiry curricula. Hands-on performance assessment, in which 1000 fifth-grade students were involved from nine school districts in the USA, showed little or no curricula effect; however, it was not completely clear whether the lack of difference in the performance assessments was a consequence of the assessment, the curricula and/or the teaching (Pine et al., 2006). Results of a study in which 18 American middle school students with serious emotional disturbance were instructed over the course of eight weeks on “Matter” using two different approaches indicate that students in the hands-on instructional programme performed significantly better than students in the textbook programme in two of the three measures of science achievements: a hands-on assessment and a short-answer test (McCarthy, 2005). Also, the research findings of O'Neill and Polman (2004) on three different cases of student-centred science activities (student-designed project work, sustained on-line work with volunteer scientists, and involving students in the formulation of research questions and data analysis) showed that these activities substantially contribute to the achievement of the scientific literacy goals and competences promoted in the educational standards. A study by Chiu et al. (2002) revealed that the positive effects of the hands-on approach in teaching and learning science on deeper understanding of scientific concepts and mastering science competences can be further strengthened by inclusion of the main features of cognitive apprenticeship (i.e., coaching, modelling, scaffolding, articulation, reflection, and exploration) in the hands-on approach. Thirty grade-ten students participated in the study, 10 in the control group and 20 in the treatment group. Both groups were presented with a series of hands-on chemical experiments on equilibrium. The students in the treatment group were instructed on the basis of the main features of cognitive apprenticeship, while the control group learned with a tutor without explicit cognitive apprenticeship. The students in the treatment group were able to construct correct models of chemical equilibrium, and their achievements significantly outperformed those of the control group.

An additional variable that affects students' science achievements through hands-on approach activities is the frequency of exposure to hands-on experience. Data collected by the National Education Longitudinal Study of 1988 in the USA on a nationally representative sample of grade-eight students were analysed in order to find the relation between the amount of time students spent experiencing hands-on science and their science achievements (Stohr-Hunt, 1996). Significant differences were found across the hands-on frequency variable with respect to science achievement. Students who were engaged in hands-on activities every day or once a week scored significantly higher in the standardised test of science achievement than did students who were exposed to hands-on activities once a month, less than once a month or not at all (Stohr-Hunt, 1996). A study of the effects of inquiry-based teacher practices on science excellence and equity (Von Secker, 2002) showed that teaching practices that improve students' overall academic excellence are simultaneously as likely to contribute to greater inequities among more and less advantaged students as they are to close persistent achievements gaps.

In teaching and learning chemistry, hands-on supported laboratory work is of special importance, due to the abstract language and symbolism of chemistry, which calls for establishing links between the theoretical (abstract) and observable (practical) content of topics taught (Flick, 1993; Devetak and Glažar, 2010). In addition, through hands-on laboratory work, learning goals such as subject-matter mastery, improved scientific reasoning, an appreciation that experimental work is complex and can be ambiguous, and an enhanced understanding of how science works, can be achieved (Moore, 2006). The hands-on approach to laboratory work also enables the development of a series of generic competences and skills, such as manipulation of the equipment, experiment design, observation and interpretation, data collection, processing and analysing, problem solving and critical thinking, communication and presentation, developing safe working practices, time management, ethical and professional behaviour, application of new technologies, and team work (Buntine et al., 2007). Despite efforts to incorporate laboratory exercises and other inquiry-based learning strategies, many, if not most, science classrooms remain places in which students receive parcels of pre-packaged knowledge from their teachers through direct transmission and/or carefully orchestrated learning activities (Sadler et al., 2010).

The impact of students' motivation on their learning and academic achievement

A series of research outcomes have proven that not only teaching strategies but especially autonomous academic motivation is positively associated with academic achievements (e.g., Grolnick et al., 1991; Fortier et al., 1995; Guay and Vallerand, 1997; Cavallo et al., 2003; Glynn et al., 2007; Gungor et al., 2007; Rattelle et al., 2007). Research is fairly consistent in showing that motivation influences cognitive and metacognitive processes amongst students and thus stimulates higher forms of thinking and determines the individual’s attitude and approach to learning and to activities that lead to creative (learning) achievements (e.g., Rheinberg et al., 2000; Jarvela and Niemivirta, 2001; Schunk and Zimmerman, 2008).

Most theories have treated motivation as a unitary concept that varies in amount; however, by contrast, the Self-Determination Theory (SDT) of motivation (Ryan and Deci, 2000a, 2000b; Deci and Ryan, 2008) has provided new insights into, and revealed new dimensions of motivation. The theory focuses on motivational orientations or types rather than just the amount of motivation, paying particular attention to autonomous motivation, controlled motivation, and motivation as a predictor of performance, relational, and well-being outcomes (Deci and Ryan, 2008). Motivation is thus defined as a multidimensional concept that varies in terms of quality. Student motivation is of high quality when primarily based on autonomous motivation (i.e., intrinsic, identified and integrated regulations), but it is of poor quality when based on controlled motivation (i.e., external and introjected regulations) (Guay et al., 2008a). In addition, research findings (Guay et al., 2008b) have revealed that some types of motivation are subject specific whereas others are not; for example, intrinsic motivation differs in intensity for maths, writing and reading. Furthermore, autonomous motivation has been found to be more in evidence when students experience satisfaction of their basic psychological needs for competence, relatedness and autonomy. Examination of different aspects of SDT in the domain of education (Chirkov and Ryan, 2001; Vansteenkiste et al., 2004) has shown that in classrooms in which teachers are autonomy supportive, students are more intrinsically motivated, as well as feeling more competent at school work and thus having a higher self-concept. The autonomy-supportive style of teaching also leads to greater learning performance outcomes than the controlling style. The autonomy-supportive style of teaching is primarily related to a relaxing classroom atmosphere, which, according to neuropsychological research studies, is crucial for effective learning to occur (Stone et al., 1998; Aggleton and Young, 2002; Phelps, 2006). The research of Vansteenkiste et al. (2009) was focused on the application of cluster analysis for identification of the motivational profiles of students based on the dimensions of autonomous and controlled motivation. A cluster analysis in their sample revealed four motivational profiles: a good quality motivation group (i.e., high autonomous, low controlled); a poor quality motivation group (i.e., low autonomous, high controlled); a low quantity motivation group (i.e., low autonomous, low controlled); and a high quantity motivation group (i.e., high autonomous, high controlled). The good quality motivation group displayed the most optimal learning pattern and scored highest on perceived need-supportive teaching.

The research hypotheses

Based on a summary of theoretical considerations and following the research questions two hypotheses were established: (1) Students' motivational orientation is related to their chemistry achievements (i.e., prior chemistry achievement and chemistry knowledge, experiential and hands-on knowledge), and (2) Students' motivational orientation is related to their perception of the didactical aspects of the hands-on approach to visible spectrometry (e.g., workbook design, learning climate, teacher's guidance, communication within groups, etc.), and to specific knowledge and skills gained through this approach (e.g., the correlation between the colour of matter and absorption, LED selection, the role of blank, etc.). Recommendations for teachers made from the results of the study would encourage teachers to use the hands-on approach in teaching chemistry more frequently and with greater professional self-confidence (Ryan and Deci, 2009).

Method

Participants

The sample included 295 students from Slovenian and Polish vocational and technical high schools; more specifically, vocational schools for food processing, chemistry and laboratory medicine, and for pharmacy, cosmetics and health care. All of the students were involved in the Leonardo da Vinci project “The hands-on approach to visible spectrometry for vocational schools II” (Vrtačnik et al., 2011). The average age of the participating students was 18.2 years–59% females (N = 174) and 41% males (N = 121). The educational systems in Slovenia and Poland (EURYDICE, 2008) have several similarities and face several similar problems. In both countries, people in VET gain the impression of being pushed to the sidelines in some aspects and to some extent. In both countries, there is a tendency for a significant proportion of students who might have enrolled in VET, and used to enrol in the past, now preferring to seek places in general education; this gives them the opportunity to postpone the choice of their prospective career and guarantees them the smoothest progress towards tertiary educational with no prior limitations or restrictions. Students from both participating countries did not differ statistically in their basic knowledge of visible spectrometry; therefore, the condition of sample homogeneity was guaranteed (t = 1.56, df = 275, p ≥ 0.05).

Measures

Students' motivational orientation and perception of learning. Students' motivational orientation and their perception of the hands-on approach to visible spectrometry were assessed by a 37-item questionnaire that was constructed for the purpose of the study on the basis of two questionnaires used in previous research (Black and Deci, 2000; Juriševič et al., 2008). Its theoretical background was educational psychology research on motivation and self-concept (Marsh, 1990; Ryan and Deci, 2000b). Specifically, the instrument was designed to assess: (1) different components of students' motivation for learning chemistry, i.e., controlled motivation based on extrinsic motivational stimuli, regulated motivation based on internalised and integrated motivational stimuli, intrinsic motivation based on internal motivational stimuli, and academic self-concept, based on perception of competence in chemistry learning (i.e., chemistry self-concept), (2) students' perception of their preference regarding the instructional method used in the study, and (3) students' perception of the specific knowledge and skills gained through the hands-on approach to visible spectrometry (see Appendix). In line with a specific purpose of this study the questionnaire was assumed to be logically valid instrument (i.e., content validity; American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999). For the purpose of this study the internal consistency for the items was verified with the calculation of the Crombach's α coefficient (Table 1) and considered satisfactory (Cronbach and Shavelson, 2004).
Table 1 Internal consistency for the questionnaire subscales and related items
Questionnaire subscales Cronbach's α coefficient Questionnaire items (see Appendix)
Controlled motivation 0.63 1,2,6,7,9,10,11,15,16
Autonomous motivation—regulated 0.71 3,4,5,8,12,13,14
—intrinsic 0.72 17,18,19,20
Chemistry self-concept 0.86 21,22,23,24
Perception of instructional methods used 0.76 25,26,27,28,29,30,31
Perception of knowledge and skills gained 0.75 32,33,34,35,36,37

Administration of the questionnaire took approximately 15 min in the classroom; students were asked to respond to a simple declarative sentence on a 5-point rating scale, ranging from 5—very true for me, to 1—not at all true for me. The scoring system following the work of Ryan and Connell (1989) and Marsh (1990) was used for the computation of four composite variables (i.e., controlled, regulated, intrinsic motivation and self-concept), while items measuring the students’ perception of different instructional methods used and specific knowledge and skills gained through hands-on approach were descriptively analysed by each item separately (see Appendix).

In order to identify the number of clusters in the data set based on the motivational dimensions defined by controlled, intrinsic, regulated motivations and self-concept, k-means clustering was used. K-means clustering is a method of cluster analysis that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. The means for each cluster on each dimensions and F values from the analysis of variance on each dimension were used as indications for assessment of how distinct different k clusters are (StatSoft, 2010). The greatest differences between means for three of the four dimensions of clustering from the analysis of variance performed for each of the dimensions were obtained for the k-2 clustering procedure. Therefore, in further analysis, we decided to use the results of k-2 clustering of the data set based on four dimensions (intrinsic motivation, self-concept, controlled and regulated motivation). The final cluster centres and number of cases in each cluster are presented in Table 2. The cluster analysis confirmed two motivational orientations: Cluster I was identified as a low quantity motivation group (i.e., low autonomous (intrinsic and regulated) motivation, low controlled motivation, and lower self-concept), and Cluster II was identified as a good quality motivation group (i.e., high autonomous, low or average controlled motivation, and higher self-concept) (Vansteenkiste et al., 2009).

Table 2 Final cluster centres
Dimension Cluster
I—low quantity II—good quality
Intrinsic motivation 2.18 3.61
Regulated motivation 2.80 3.87
Controlled motivation 2.98 3.01
Self-concept 2.45 3.87
No. of cases in each cluster 163 132

Data were analysed using descriptive and inferential statistics; frequencies, percentage, mean, standard deviation, and t-test was calculated in SPSS Version 16.0 program. Different sample sizes for each analysis result from the fact that SPSS did not included cases (subjects) with missing values occurred because of nonresponse on the variable(s) under analysis (Schafer and Graham, 2002).

Students' chemistry knowledge and achievement. Students' final chemistry grades from the previous school year were used to determine prior chemistry achievement (5-point rating scale from 5—excellent to 1—insufficient). For assessment of knowledge of visible spectrometry, an experiential knowledge test (EKT) with 12 multiple choice and open-ended items, and a hands-on knowledge test (H-OKT) with 20 multiple choice and open-ended items were designed and semi-standardised for the purpose of the research (see below). The EKT test assessed students' knowledge from visible spectrometry gained through personal experiences with light and colour, while the H-OKT was used to assess students' knowledge from visible spectrometry gained through the hands-on approach. Internal consistency of the items from EKT and H-OKT estimated using Crobach's alpha coefficient indicated that both knowledge tests are satisfactory reliable instruments (i.e., αEKT = 0.68 and αH-OKT = 0.80).

The construction of both tests was conducted as a preliminary study in which a group of 30 students and two teachers participated. Both tests were semi-standardised through item analysis; test items with facility factor of around 0.5 and discrimination coefficient ranging between 0.3 and 1 were selected for the final tests. The following basic concepts were included in the EKT: conditions for colour perception, additive mixing of coloured beams of light, the effect of the dilution of a coloured solution on concentration and colour intensity in relation to the direction (horizontal and vertical) of the observation of coloured samples and the volume of the sample. Our assumption was that the majority of the concepts should be known to the students either from their personal experience or from previous experimental work in school. The selection of the concepts included in the H-OKT was based on the knowledge structure of the four modules selected from the hands-on approach to visible spectrometry. We were specifically interested in students' understanding of the following concepts: transmittance in relation to the concentration of the samples, the length of the light path through the sample, the relation between transmittance and absorbance, the usage of a calibration line for the determination of concentration, the composition of the blank in relation to the composition of the sample, and selection of the light emitter LED in relation to the colour of the sample. Four test items regarding the additive mixing of light beams of different colour and the effect of the dilution of the coloured solution on colour intensity in relation to the direction of observation were the same in the EKT and the H-OKT.

Research design

The research was designed in several steps, following the work plan of the project. The hands-on approach to visible spectrometry was presented to the students by 13 experienced teachers with an average of 14.5 years of teaching chemistry and/or chemistry-related subjects at vocational and technical high schools. The selected teachers participated in workshops organised at the University of Ljubljana and the University of Gdansk. At the workshops they were introduced to the Spektra™ instrument and its use in teaching selected concepts from visible spectrometry. Special attention was devoted to the four modules that had been chosen to be introduced to students through the hands-on approach: “The Colour of Substances and Light Transmittance”, “The Measurement of Light Transmittance”, “The Spectrometric Determination of Concentration”, and “The Practical Application of Visible Spectrometry”, (Gros et al., 2005; Vrtačnik et al., 2011).

Prior to the practical work with the modules, students' knowledge of visible spectrometry gained through personal experiences was tested with the EKT. After completion of the four modules, the H-OKT and the Students' Motivational Orientation and Perception Questionnaire were applied. All of the instruments were administered within regular chemistry classes. EKT and H-OKT tests were assessed by two Slovene evaluators and two Polish evaluators following standard assessment procedure agreed upon at the project partners meeting in Gdansk, Poland, by means of determined template for scoring based on expert validity, which omitted the potential differences between evaluators' scores.

The study started in January 2009 and ended in June 2010. Teachers from the participating schools were free to select within the defined time span the exact date when they would start presenting the modules and submitting tests. Each module started with a number of hands-on activities. For example, the module “The Colour of Substances and Light Transmittance” started with measuring light transmittance of a violet and yellow filter foil by using green, blue and red LED. From these observations, students had to determine which colour of light was more or less transmitted and then had to explain their observations. Through seeking a sound explanation of the results, students developed a foundation for understanding the principle that a coloured substance (absorption medium) retains the light of a complementary colour most and transmits the light of other colours relatively well.

Results

Students' motivational orientations and their relation to chemistry achievements

The relation between students' motivational orientations and their chemistry achievements (i.e., prior chemistry achievement and knowledge from visible spectrometry gained through personal experience with light and colour and through the hands-on approach) is shown in Table 3.
Table 3 Differences between clusters regarding students' chemistry achievements
Measures Cluster I Cluster II t df p
M SD M SD
Prior chemistry achievement 3.32 0.85 3.75 0.75 −3.35 151 0.001
EKT 64.44 17.57 68.64 20.84 −1.88 293 0.061
H-OKT 59.63 59.63 69.63 20.23 −4.18 293 0.000

For prior chemistry achievement, a statistically significant difference between the two motivation groups was found at p = 0.001; the average chemistry grade for the low quantity motivation group (Cluster I) was M = 3.32 with SD = 0.85 on the five-point rating scale, and for the good quality motivation group (Cluster II) it was M = 3.75 with SD = 0.75. The difference between both groups of students (i.e., Cluster I and Cluster II) in the EKT was not statistically significant (t = −1.88, df (293), p = 0.061). However, a statistically significant difference between the low quantity motivation group and the good quality motivation group was found for achievement in the H-OKT (p = 0.000); for the low quantity motivation group, the average assessment score was M = 59.63 with SD = 20.6, while for the good quality motivation group it was M = 69.63 with SD = 20.23.

In the H-OKT, the good quality motivation group of students (Cluster II) outperformed the low quantity motivation group (Cluster I) particularly in solving test items where a higher Bloom's knowledge category had to be applied (i.e., application, interpretation, and analysis; Anderson and Krathwohl, 2001), and in relation to mathematical competencies (e.g., drawing graphs and deriving results from them, or understanding the meaning of linear and exponential data relations). Statistically significant differences in performance of the low quantity and good quality motivation groups were found for the following concepts and their relations: (1) defining the relation between the colour of light and wave lengths (t = −3.00, df (293), p = 0.003), (2) explaining LED selection for measuring the transmittance of orange absorption medium (t = −2,237, df (293), p = 0.026); (3) deduction of the colour of filter foil from its transmittance graph for red, green and blue LED (t = −3.45, df (293), p = 0.001); (4) selection of the LED with the highest absorbance for a coloured filter foil (t = −2.31, df (293), p = 0.022); (5) the influence of an increasing number of filter foils on transmittance (t = −2.04, df (293), p = 0.042); (6) drawing graph T/c (mmol/L) from graph A/c (mmol/L) (t = −2.71, df (293), p = 0.007); (7) selection of a blank for measurement of the transmittance of an indicator dye that is dissolved in 1% aqueous solution of hydrochloric acid (t = −3,13, df (293), p = 0.002); (8) explaining limitations in the use of a displayed calibration line in relation to the concentration of the absorption media (t = −2.88, df (293), p = 0.004); and (9) the effect of dilution of the coloured solution on colour intensity in relation to the direction of observation—horizontal (t = −2.84, df (293), p = 0.005).

The relation between students' motivational orientation and their perception of the hands-on approach to visible spectrometry

The research focus was further on the relation between the two motivational orientations and the students' perception of various didactical aspects of the hands-on approach to learning visible spectrometry (i.e., the suitability of the workbook and the teacher's intervention, group work, relaxing climate, learning impact, the hands-on approach to carrying out experiments), as well as the contribution of the modules undertaken to specific (hands-on) knowledge and skills (i.e., understanding the relation between the colour of matter and the absorption of light, selection of the LED for measuring the transmittance of the absorption medium, the relation between transmittance and absorbance, the application of visible spectrometry to the determination of concentration).

Group statistics for the students' perception of the didactical aspects of the four modules undertaken for the low quantity motivation group (Custer I) and the good quality motivation group (Cluster II) and the results of inferential statistics are displayed in Table 4.

Table 4 Students' perception of the didactical aspects of the modules undertaken on visible spectrometry between clusters
Didactical aspects Cluster I Cluster II t df p
M SD M SD
Workbook 3.16 1.11 3.33 1.19 −1.179 261 0.240
Teacher's support 3.36 1.07 3.76 1.13 −3.6 261 0.003
Group work 2.64 1.16 3.19 1.34 −1.441 261 0.151
Relaxing climate 3.67 1.03 3.87 1.21 −3.94 261 0.000
Learning with understanding 3.54 1.12 4.07 1.02 −4.67 258 0.000
Hands-on approach 3.08 0.96 3.67 1.05 −3.11 260 0.002

Students classified in the good quality motivation group (Cluster II) appreciated the teacher's guidance of the experimental work, the relaxing yet productive climate that prevailed during learning through the modules, the approach to learning with understanding, and the hands-on approach they were exposed to, more than did students from the low quantity motivation group (Cluster I).

Group statistics and the results of the t-test of students' perception of knowledge and skills gained through the hands-on approach for the low quantity motivation group (Cluster I) and good quality (Cluster II) motivation group are given in Table 5.

Table 5 Students' perception of knowledge and skills gained through the modules undertaken on visible spectrometry between clusters
Concepts and contents Cluster I Cluster II t df p
M SD M SD
Colour of matter and absorption of light 2.91 1.04 3.66 1.11 −5.61 261 0.000
LED selection 3.20 1.05 4.24 3.82 −3.13 261 0.002
Understanding the role of the blank 3.42 1.12 3.92 1.08 −3.66 261 0.000
Handling the instrument Spectra™ 3.55 1.06 3.90 1.16 −2.54 260 0.012
T/A relation 3.11 1.02 3.75 1.09 −4.89 261 0.000
Impact on self-confidence 3.06 1.04 3.57 1.14 −3.83 260 0.000
Spectrometry usage 3.22 0.99 3.97 0.95 −6.17 260 0.000

The good quality motivation group of students (Cluster II) stated that the approach enabled them to better master the specific knowledge and skills from visible spectrometry (i.e., the relation of the colour of matter and light absorption, selection of the appropriate LED for measurement of transmittance, the role of the blank in the measurements, the relation of transmittance and absorbance and the usage of spectrometry for the determination of concentration, and handling the instruments and materials). Differences in the mean values of points assigned to the specific knowledge and skills gained are statically significant at p < 0.01 (Table 4). This result is also confirmed by the differences between the two motivation groups of students in scores achieved in the H-OKT (see Table 3).

Discussion and implications

The present study is part of a large Leonardo da Vinci project (Vrtačnik et al., 2011) that was aimed at adding new perspectives for the improvement of teaching and learning of analytical chemistry at vocational schools. In spite of some of the methodological shortcomings of the study from the research point of view (e.g., implementation of the innovation without a control group, measurement of teachers' variables, longitudinal approach, etc.), the research findings attest to the basic validity of the study, as the results clearly confirm the findings of several earlier studies related to motivation in science education (Hartas, 2010). However, the most challenging issue of the study lies in the originality of the contribution of the new approach—the hands-on approach to visible spectrometry—and therefore the involvement of the new area of motivation research, which confirms and additionally supports the scientific paradigm of the universality of academic motivation process dynamics. Nevertheless, the research findings imply many new research questions and stimulate reflection on how to enhance students’ motivation to learn with understanding in school, especially with more complex and abstract content and with students who are poorly motivated for school learning (Ryan and Deci, 2009).

Students' motivational orientations and their relation to chemistry achievements

The research findings reveal that chemistry achievements (i.e., prior achievement by means of school grades as well as the achievement in the H-OKT) are related to the quality of students' motivation and their subject-specific self-concept (i.e., chemistry self-concept), thus confirming our first hypothesis. Students with good quality motivational orientation (Cluster II) attained higher prior chemistry achievement (i.e., final chemistry grades from the previous school year) and demonstrated better knowledge in the H-OKT (i.e., hands-on knowledge) than students with low quantity motivational orientation (Cluster I). This difference between the two groups of students was especially evident in solving test items where more complex reasoning had to be used and mathematical competencies applied. In contrast, results from the EKT show that there was no statistically significant difference between the two motivational orientation groups with regard to the students' chemistry knowledge gained through personal experience with light and colour before the implementation of the hands-on approach, when students started to learn selected concepts from visual spectrometry by seeking correlations between experimental observations and theory through the hands-on approach. Students with good quality motivational orientation improved significantly better in their knowledge by learning within the hands-on approach than their schoolmates with poor quantity motivational orientation. This result could imply that students who develop strong autonomous motivation and a stable self-concept during schooling achieve higher levels of conceptual knowledge than their classmates with a more controlled motivational orientation and less academic self-confidence; in other words, they are probably willing to learn with understanding in motivationally and cognitively appropriate learning situations, as was the case with the implementation of the hands-on approach in our study. The finding could be supported by the results of the study by Lewis et al. (2009) who reported that self-concept plays an important role in student performance on the outcome measure, indicating the affective domain does play a role that is separate from conventional cognitive measure.

The results are in line with other studies in which a positive correlation between autonomous motivation and good academic achievements has been identified (Boiche et al., 2008; Deci and Ryan, 2008). We could presume the hands-on approach experienced by students while working with modules from visible spectrometry offered primarily students with high autonomous motivation (Cluster II), the freedom to explore and search for explanations of the experimental results on their own without the constant guidance of the teacher, thus creating a working climate that stimulated their learning process (Cornelius-White, 2007). However, for more valid conclusion further research in this field with inclusion of other variables (i.e., instructional environment or/and strategies) are needed. The differences in academic achievements between the two identified motivational orientations of students in our study could be additionally explained by the differences in their self-concept. Namely, the good quality motivation group of students believed more strongly that they could do well in chemistry (i.e., they perceived themselves as competent learners in the chemistry class) since their mean value of chemistry self-concept was higher than the chemistry self-concept of the students from the low quantity motivation group (see Table 2). This result confirms a series of research findings where self-concept has been found to be an important mediator of all types of achievement-related behaviours (Pajares, 1996; Schunk et al., 2008; Bong and Skaalvik, 2003; Lewis et al., 2009; Sandoval and Harven, 2011).

The impact of students' motivational orientations on their perception of the hands-on approach to visible spectrometry and specific knowledge and skills gained through the modules

The results of the study also confirmed the second hypothesis about the relation of students' motivational orientations and their perception of the hands-on approach to visible spectrometry and specific knowledge gained. Students classified in the good quality motivation group (Cluster II) were more appreciative of the teacher's guidance in the experimental work, the relaxing yet productive climate that prevailed during the work, the impact of the approach on their knowledge of visible spectrometry, and the hands-on approach they were exposed to than were students from the low quantity motivation group (Cluster I). Majority of differences in the mean values of points assigned to the selected elements of the didactic approach are statistically significant at p < 0.01 (Table 4). The good quality motivation group of students further stated that the hands-on approach enabled them to better master the specific knowledge and skills from visible spectrometry (i.e., the relation of the colour of matter and light absorption, selection of the appropriate LED for measurement of transmittance, the role of the blank in the measurements, the relation of transmittance and absorbance and the usage of spectrometry for the determination of concentration, and handling the instruments and materials). Differences in the mean values of points assigned to the specific knowledge and skills gained are statistically significant at p < 0.01 with exception of “handling the instrument Spectra™” at p < 0.05 (Table 5). This result could be also confirmed by the differences between the two motivation groups of students in the mean values of scores achieved in the H-OKT (see Table 3).

Based on the fact that participating students gained knowledge of basic concepts of visible spectrometry through hands-on approach, we can assume that these results are in accordance with the findings of Moore (2006), who found out that hands-on laboratory work enables the achievement of a series of learning goals, among them subject-matter mastery and better reasoning. The research of O'Neill and Polman (2004) also revealed that student-centred science activities contribute to better academic achievements, since they improve scientific literacy. The possible reason that the good quality motivation group of students profited more than the low quantity motivation group is that student-centred activities support autonomous learning, which better suits students with higher autonomous motivation (Chirkov and Ryan, 2001; Vansteenkiste et al., 2004; Palmer, 2009).

However, it is reasonable to infer that more frequent applications of student-centred activities in the classroom would enhance the students' motivational profile, especially the regulated incentives derived from active learning pedagogy that lead to learning with understanding in motivationally supporting environment (Cornelius-White, 2007; Lewis et al., 2009). Nevertheless, we could conclude that the hands-on approach supports an autonomous teaching style (Deci and Ryan, 2009), which could, if used more frequently, support satisfaction of the needs for autonomy, competence and relatedness which will lead to students not only to be more intrinsically motivated but also to be more effective in internalizing and integrating extrinsic motivation so as to be more cooperative and volitional overall. Deci and Ryan (2002) point out the fact that different approaches even often used and well intended are actually ineffective in order to improve academic achievement by stimulating intrinsic motivation and supporting the perceived autonomy of students (i.e., implementing stringent new testing programs, giving large amounts of homework, putting much emphasis on rewards, punishments and controls, and using controlling and pressuring language). The authors show that these strategies will lead to substantial motivational and emotional loss and high-quality achievement (like conceptual learning, creativity and flexible problem solving) will suffer too for the majority of the students. On the other hand the authors outline eight tips that by their opinion are the most effective to improve education and academic achievements by stimulating autonomous motivation and therefore should be addressed more carefully in the future; these tips are: (1) providing choice, (2) encouraging students' experimentation and self-initiation, (3) foster students' willingness to take on challenges, explore new ideas and persist at difficult activities, (4) offering optimal challenges (neither too easy, nor too difficult), (5) providing feedback that is not evaluative of the person, (6) giving a meaningful rationale for requested behaviour, (7) acknowledging feelings, and (8) setting up cooperative learning opportunities.

Finally, the present study highlighted the need for replication studies and especially more complex research on the field, and also opened new directions for further research, such as: What changes in the students' motivational orientations would be detected if students had the possibility to experience the hands-on approach in learning science more frequently? Does the hands-on approach in science teaching contribute to the permanence and quality of knowledge? Could the hands-on approach to science teaching contribute to changes in science attitudes and values?

Appendix

Items from the Students' Motivational Orientation and Perception Questionnaire–Form C—Chemistry (Juriševič and Vrtačnik, 2010)

Try to express your past opinions about why you learned chemistry:

(1) I learned in order to fulfil the expectations of my teachers and parents, so that they did not pressure me with constant complaints.

(2) I learned because I did not want to be ashamed in front of my classmates and I did not want to be known as a bad student.

(3) I learned because for me it was important to know certain things and to get good grades.

(4) I learned because the content was interesting and because I generally enjoy learning.

This year I put extra effort into learning chemistry because:

(5) In this way I will have an opportunity to improve my understanding of the topics discussed.

(6) Otherwise my teacher, parents and peers will get a bad impression of me.

(7) I would like to be proud of my achievements and high grades at the end of the course.

(8) A solid knowledge of chemistry is important for my life and future professional development.

In the chemistry classroom, I take the teacher's recommendations and guidelines into consideration because:

(9) If not, I could get a bad grade.

(10) Otherwise I will be afraid that I am not doing things correctly.

(11) It is much easier to follow the teacher's instructions than to work independently.

(12) I am convinced that the teacher knows best how to learn a particular topic.

This year, I will learn chemistry because:

(13) I found the topics discussed interesting and would like to learn more about them.

(14) I found the topics discussed challenging and helpful for solving real life problems.

(15) I would like to get a high grade in chemistry.

(16) I would like to show others how good I am at studying chemistry.

(17) The new problems that I encounter in learning chemistry represent an additional challenge for me.

(18) Even during my spare time I like to occupy myself with chemistry.

(19) For me, chemistry is simply interesting.

(20) I simply like to learn chemistry.

(21) I am good at chemistry.

(22) If I compare my knowledge of chemistry with that of my peers, my knowledge is better.

(23) My chemistry grades are very high.

(24) By learning chemistry I could achieve a high level of understanding.

The modules from “The hands-on approach to visible spectrometry” that we studied thoroughly in the classroom are interesting because:

(25) The instructions in the Student Book are very clear and therefore very easy to follow.

(26) During the experiments the teacher always followed our work and the results we obtained, thus giving us the necessary incentive.

(27) We worked in a small group within which we could help each other, as well as comparing our results with other groups.

(28) There was a relaxing and yet productive atmosphere in the classroom.

(29) I finally understood some concepts that so far had not been clear to me.

(30) Learning was based on doing experiments and not only listening and taking notes based on the teacher's explanations.

I found the studied modules challenging because:

(31) I finally understand how the colour of matter is related to the absorption of light.

(32) From the experiments undertaken I gained experience of how to choose an appropriate LED for measuring the transmittance of the absorption medium.

(33) I know why it is necessary to adjust the transmittance to 100% with the selection of an appropriate blank before taking measurements of selected absorption medium.

(34) I found that working with the Spektra™ spectrometer is simple and that the experiments were interesting.

(35) Based on the experiments undertaken I understand the relation between transmittance and absorbance.

(36) I was successful in conducting experiments and I also gained a lot of self-confidence for future experimental work.

(37) I understand how it is possible to determine the concentration of substances with the use of spectrometry.

Acknowledgements

The authors wish to thank the Leonardo da Vinci financing fund, and all of the participating students and their teachers. Without their dedication and trust this research would not have been possible.

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