View PDF VersionPrevious ArticleNext Article
 
DOI: 10.1039/C8RP00079D (Paper) Chem. Educ. Res. Pract., 2018, 19, 819-833

The effect of concept maps, as an individual learning tool, on the success of learning the concepts related to gravimetric analysis

N. Turan-Oluk * and G. Ekmekci
Department of Mathematics and Science Education – Chemistry Education, Gazi University, Ankara, Turkey. E-mail: nurcanturan@gazi.edu.tr; guler@gazi.edu.tr

Received 16th March 2018 , Accepted 2nd May 2018

First published on 3rd May 2018

Abstract

This study aims to conduct a detailed investigation on the effect the use of concept mapping, as an individual learning tool, has on students’ success in learning the concept of gravimetric analysis. This study applies a case study research design to quantitatively examine the effect of the use of concept mapping and to conduct a detailed qualitative investigation of the participants’ opinions about its use. In this study, the concept maps were used both as a data collection tool [Select and fill in the nodes (SAFIN); Select and fill in the lines (SAFIL); Create and fill in the lines (CAFIL); Select and fill in the nodes&lines (SAFIN&L)] and as an individual learning tool. For data triangulation, students’ opinions on the concept mapping technique, as an individual learning tool for understanding gravimetric analysis, were also taken. Results from the study showed that there were significant differences between the pre- and post-test scores on all the tests (four types of fill-in-the-blank concept maps and a concept test) in favor of the post-test scores. In other words, the use of the concept map resulted in an increase in the success of the students. Furthermore, the participants expressed very positive opinions about the concept maps as an individual learning tool, both on the attitude scale and in their written opinions, declaring that it has a definite boosting effect on successfully learning a concept.

1. Introduction

The research conducted on science teaching has revealed that a majority of science knowledge is acquired through rote-learning and does not necessarily reflect factual information (Nakhleh, 1992; BouJaoude and Barakat, 2000). There are two primary reasons for this, namely the difficulty involved in understanding the more abstract and conceptual nature of science, and the ineffectiveness of the teaching methods applied. These problems create serious barriers to teaching, especially chemistry teaching. Chemistry is regarded as a highly challenging subject to learn on account of its unique language and abstract mathematical structure and the many concepts which need to be ideated (Gabel, 1999).

In looking at the history of teaching science, it can be seen that although there have been many methods proposed, traditional methods continue to be the most widely preferred, resulting in students being inclined towards the rote learning process. The knowledge gained through rote learning fails to be permanent due to the fact that it is not readily associated with a person's previously possessed knowledge (Novak, 1998; Martínez et al., 2016). This process, therefore, is incompatible with the prime purpose of education, which is to establish permanent and meaningful understanding. According to Ausubel's learning theory, meaningful learning can only be achieved if a person associates newly learned concepts with ones that already exist in his/her mind (Seel, 2012). Mintzes et al. (2000) reported a similar conclusion, stating that meaningful learning takes place when students try to associate newly introduced concepts and proposals with ones already present in their minds. The purpose of conceptual teaching is to correctly position concepts in the students’ minds so that they would be better able to associate these concepts with already existing ones (Ayas, 2005). If a student is able to apply the concepts he/she has learned to different circumstances in his/her own words and then adapts them to the new conditions, he/she is assumed to be a learned person or a person who has conceived the subject (Sözbilir and Neacşu, 2014). For this purpose, concept maps are considered to be one of the most effective teaching method (Novak, 1998).

The use of concept maps is a method, based on Ausubel's meaningful learning theory, that was introduced by Novak in the 1970s (Novak and Gowin, 1984; Novak and Musonda, 1991). The concept map is a two-dimensional diagram that allows a person to identify the concepts and the relationships between the concepts that exist in his/her mind (Ruiz-Primo et al., 2001a; Safayeni et al., 2005). Concepts and interrelationships are the basic components of the concept map. Two concepts are connected to each other via a linking line, and the words that express the relationship between the concepts and the so-called linking phrase are written down (Novak and Cañas, 2006).

On a concept map, the relationship that exists between two concepts is called a proposition, which is considered a basic component of the concept map (Novak and Gowin, 1984; Ruiz-Primo et al., 2001a).

Concept maps can be used to help students understand chemistry subject matters and concepts. They are used as a teaching method by which connections and relations, as well as the hierarchy of concepts, are presented in a clear, concise way (Sisovic and Bojovic, 2000). The use of concept maps is not only an effective way to perform concept teaching, but it is also able to clearly exhibit the relations between concepts. Overall, they are one of the most successful tools for establishing meaningful and permanent learning (Martínez et al., 2016).

Concept maps are visual graphics that organize the information used in carrying out different educational purposes, like learning strategy, teaching method and measurement tools (McClure et al., 1999). According to the constructivist learning theory, educators can use the concept maps as a teaching tool in place of rote learning to achieve more meaningful and permanent learning levels (Novak and Gowin, 1984; Mintzes et al., 2000; Novak and Cañas, 2006; Conradty and Bogner, 2010). According to Ausubel, effective teaching should follow a hierarchy that starts from basic subjects to more specialized, complex topics. Concrete models, graphics, schemes and simulations are especially very helpful for visualizing and coding the relations between the main dimensions and subdimensions of the information. In this context, concept maps, which present complicated inter-conceptual relations in a hierarchical manner, going from general concepts to special concepts, is one of the teaching materials which can be used to ensure effective teaching and/or to help students reach higher learning levels (Kurada, 2006).

Concept maps present information in a straight-forward manner without having to sacrifice the complexity or expression of the information. With concept maps, a visual image, in contrast to a verbally-generated conceptualization, of the concept and inter-conceptual relations is able to be produced to facilitate a clearer understanding of the subject matter presented (Gul and Boman, 2006). Concept maps help the students to understand how the concepts are implanted in their minds during the learning process. In addition to all these advantages, concept maps, because they present the information in a visual manner, enable people to accurately organize the information in their minds (Novak, 1998; Didiş et al., 2014). Also, it has been shown that students who have had previous experience in using concept maps had improved ability in self-regulated learning and increased levels of meaningful learning (Novak, 1998).

There are some discrepancies between the data reported in the literature concerning the use of concept maps as a teaching tool or as a personal learning tool. While some studies have reported significant differences in favor of the group using concept maps as a teaching method (Fraser and Edwards, 1985; Martínez et al., 2013; Çömek et al., 2016; Jaafarpour et al., 2016), others have shown that there to be no significant difference between the pre-test and post-test scores when a conventional expository method was used and when concept maps were used (Stensvold and Wilson, 1992; BouJaoude and Attieh, 2008; Martínez et al., 2016).

This study aims to conduct a detailed investigation of the effect of the use of concept mapping as an individual learning tool on the success of the ability of participants to understand the concepts related to gravimetric analysis.

In taking into account the views of the students on how the concept maps affected their learning, an attempt was made to present the effect of concept maps on learning as a whole.

For this purpose, the following sub problems were investigated:

How does the use of concept maps as an individual learning tool affect the success of chemistry students to understand the concepts related to gravimetric analysis?

Is there a statistically significant difference between the pre- and post- test results under these circumstances?

What are the opinions of the chemistry students on the usability of concept maps as an individual learning tool?

2. Theoretical background

2.1. Concept maps

Concept maps were developed by Novak as a result of 12 years of work, which started in 1972 (Novak and Musonda, 1991). Concept maps provide a visualization of how individuals relate key concepts in their mind (Ruiz-Primo et al., 2001a). The basic components of concept maps are the concepts and inter-conceptual relations. Concepts are generally expressed on concepts maps in the form of circular and rectangular boxes. Two concepts are connected with a line, whereon labels representing the nature of the relations are placed (Novak and Cañas, 2006). The combination of two concepts and a labeled line is designated a proposition, which functions as a major component of the concept maps (Novak and Gowin, 1984; Ruiz-Primo et al., 2001a). According to Novak and Gowin (1984), one of the most important features of the concept maps is their hierarchical structure, which is based on Ausubel's meaningful learning theory, which maintains “new information is related to the more general concepts“ (Novak and Gowin, 1984; Moon et al., 2011).

2.2. Task and response format for concept maps

The literature related to the field shows that concepts maps can be established in different formats (Ebenezer, 1992; Markow and Lonning, 1998; Ruiz-Primo and Shavelson, 1996; Ruiz-Primo et al., 2001b).

There are two general methods for establishing concept maps, namely, Construct-a-Map-from-Scratch and Fill-in-the-Map (Ruiz-Primo and Shavelson, 1996). Construct-a-Map-from-Scratch is a mapping method where the students are given the concepts or the subject and asked to establish the concept maps by themselves. Whereas, with the Fill-in-the-Map method the students are given a concept map where the concepts or relations are left blank, and the students are expected to fill in the blanks (Ruiz-Primo et al., 2001a). In this latter method, the students’ responses are marked as either right or wrong (Ruiz-Primo et al., 2001a).

Fill-in-the-blank maps can vary according to which type of map components are omitted (concepts/relation clauses or both), the percentage of the components removed (50% or more) or the dynamic of the concepts (ordered or complex) (Schau et al., 2001). In the concept-filling method, also known as select-and-fill-in-the-nodes method, the students are given maps which contain the relations and are expected to select the appropriate concepts from the list provided (Ruiz-Primo et al., 2001a).

With the fill-in-the-lines method, students are given maps where the relation clauses are erased, and they are asked to choose the most appropriate statements from the relation list provided with the maps (select and fill in the lines) or fill in the blanks with their own statements (create and fill in the lines) (Schau et al., 2001).

The final method is the use of master maps, which include partly filled-in concepts and clauses. Ruiz-Primo et al. (2001a), in their study involving partially blank concept maps, found that the concepts and relations left unanswered did not affect the overall grades of the participants. In other words, the concepts and relations left unanswered were not variables.

3. Method

3.1. Pilot study

A pilot study was performed to verify the reliability of the study and to determine any problems that may occur during this process. The pilot study was conducted in two separate stages with two different samples a year before starting the main study. In the first stage, which included the participation of 148 undergraduates, the validity and reliability analysis of the concept test was completed, as detailed in Section 3.1.1. In the second stage of the pilot study, the preparation of fill-in-the-blank concept maps and the validity and reliability analysis of these concept maps were completed, as detailed in Section 3.1.2. The second stage of the pilot study was conducted with 30 pre-service chemistry students who were different from the students that participated in the first stage.
3.1.1. The first stage of the pilot study: the development of the gravimetric analysis concept test. The Gravimetric Analysis Concept Test (GCT), used as the pre- and post-test, was developed in stages. The first stage involved a thorough literature survey on the topic of gravimetric analysis to determine the most important concepts and relations. Next, a master concept map was developed using all these concepts that covered the whole unit. The propositions in the map were arranged as 25 true/false (T/F) and multiple choice questions (10 T/F and 15 multiple questions). Two analytical chemistry experts were consulted for the validity of the test. One of the experts was from the Faculty of Education and the other from the Faculty of Sciences, and both were professors of Analytical Chemistry. The experts were asked to examine whether the scope of the test was sufficient to evaluate the concepts related to gravimetric analysis. In addition, the experts were asked to examine the prepared questions according to their conceptual content and to indicate whether any corrections were needed. The experts approved the content validity of the test after these corrections had been made.

In the next stage of development, item parameters for the GCT were investigated. The item difficulty index (p) and the item discrimination index (r) values are shown in Table 1.

Table 1 The item difficulty index (p) and the item discrimination index (r) values
Item no. p r Item no. p r
1 0.68 0.30 14 0.60 0.35
2 0.55 0.33 15 0.60 0.35
3 0.61 0.31 16 0.73 0.25
4 0.61 0.29 17 0.60 0.35
5 0.45 0.28 18 0.68 0.28
6 0.59 0.34 19 0.69 0.26
7 0.49 0.31 20 0.54 0.21
8 0.46 0.26 21 0.68 0.33
9 0.70 0.30 22 0.65 0.28
10 0.61 0.31 23 0.61 0.29
11 0.54 0.26 24 0.56 0.31
12 0.66 0.31 25 0.61 0.36
13 0.64 0.34

Osterlind (2002) states that the item difficulty index should be between 0.40 and 0.80 for achievement tests. In the current study, the difficulty indexes of the items ranged between 0.45 and 0.73.

Atılgan (2009) maintains that items with a discrimination index greater than 0.20 may be used in the test. In the current study, the discrimination indexes of the items ranged between 0.25 and 0.36.

To confirm the reliability of the test, a study involving 148 students who had taken an analytical chemistry course was conducted. Correct answers on the test were given a score of 1 while wrong answers were given a score of 0. With this scoring system, the Kuder–Richardson 20 (KR-20) method, based on item variance, was able to be used. KR-20 can only be applied in cases where the answers are scored according to a 1/0 format (Fraenkel and Wallen, 2006). A single application of this method is capable of only yielding the reliability factor of internal consistency coefficients (Kan, 2009).

Although most of the studies in the literature focus on finding the internal consistency coefficient, it has been stated that for measuring binomial items, KR-20 has to be used, while for measuring multiple items, Cronbach's alpha formula must be employed (Fraenkel and Wallen, 2006; Kan, 2009). Bademci (2011) claimed that the KR-20 formula for 1/0 scoring formats yields the same results as those of the Cronbach's alpha formula. For this test, first, the α value was calculated, which was 0.715, using SPSS 15 statistical software. Next, using the KR-20 formula for the data obtained from the 148 students, the internal consistency coefficient was calculated to be 0.719. Conveniently, the Cronbach's α and internal consistency coefficients came out to be approximately the same. Results for the reliability of the test were KR-20 = α = 0.72. An internal consistency coefficient above 0.70 indicates high reliability (Fraenkel and Wallen, 2006).

In addition, a split-half method was used for estimating reliability. The split-half procedure includes scoring two halves of a test separately and then calculating a correlation coefficient (Fraenkel and Wallen, 2006). The correlation coefficient was calculated as 0.62 for GCT. The reliability coefficient was calculated using the Spearman–Brown prophecy formula (Fraenkel and Wallen, 2006). The reliability of the scores on the total test was 0.765. The final version of the GCT is shown in Appendix I.

3.1.2. The second stage of the pilot study: formation of the concept maps.
3.1.2.1. The preparation of the master concept map. The concept maps used in the study were prepared by the researchers using Inspiration 9 software. First, 37 concepts, which are shown in Table 2, were determined to be related to gravimetric analysis.
Table 2 Tentative concept list for gravimetric analysis
The concepts are hierarchically ordered.
1. Gravimetric analysis 20. Combustion
2. Mass 21. Impurities
3. Crucible 22. Pollution
4. Constant weighting 23. Colloidal suspension
5. Quantitative 24. Crystalline suspension
6. Electrogravimetry 25. RSS
7. Precipitation gravimetry 26. Q
8. Gravimetric titrimetry 27. S
9. Volatilization gravimetry 28. Nucleation
10. Sample 29. Particle growth
11. Analyte 30. Adsorption
12. Precipitate 31. Coagulation
13. Precipitation 32. Digestion
14. Filtering 33. Coprecipitation
15. Filter paper 34. Mechanical entrapment
16. Black band 35. Mixed crystal formation
17. Blue band 36. Surface adsorption
18. White band 37. Reprecipitation
19. Washing

The concept map created on the basis of these concepts was examined by an expert in terms of the accuracy and hierarchy of the relations and the coverage of the concepts. From the results of the expert investigation, it was decided that the concepts shown in the first column of Table 3 be added to the list. Since newly added concepts can complicate the map, the concepts of secondary importance, which are shown in the second column of Table 3, were removed. Furthermore, because the concepts of adsorption and surface adsorption, as well as pollution and impurity, connotate almost the same meanings, the concepts of adsorption and pollution were also omitted from the map. The new concept map prepared with 39 concepts was examined by another expert. The final version of the master concept map is shown in Appendix II.

Table 3 The concepts newly added to the list and removed from the concept list
Newly added concepts The removed concepts
Primary adsorption layer Black band
Counter ion layer Blue band
Electrical double layer White band
Electrolyte addition Crucible
Heating Filter paper
Dilution Constant weighing
Occlusion
Particle size
Peptization


3.1.2.2. Preparation of the fill-in-the-blank concept map. The master concept map, whose final form was created based on the expert's suggestions, included 39 concepts and 41 inter-conceptual relations. Among the inter-conceptual relations, 9 of them were cross links. The fill-in-the-blank concept maps differed according to which concept map components were omitted (concept/relation/both of them), how many were discarded (50% or more) or how the gaps were located (ordered or non-ordered) (Schau et al., 2001). To create the “Select and fill in the nodes (SAFIN)” format, all the concepts, except for “gravimetric analysis” and “precipitate”, were erased from the master concept map (see Appendix III). Also, all the relation statements of the expert maps were erased and rearranged to create a “Fill in the lines (FIL)” form (see Appendix IV). The FIL form was arranged in two different formats: Select and fill in the lines (SAFIL) form, where statements are selected from the list containing the answers and Create and fill in the lines (CAFIL) form, where the statements are to be created by the participants themselves. Finally, 20 of the 39 concepts were erased and 19 of the 41 inter-conceptual relations were removed from the map to develop the “Select and fill in the nodes&lines (SAFIN&L)” format. The concepts and relations were removed from the partially blank concepts maps in an arbitrary, rather than sequential, manner, and placed on the map in such a way as to signal the anticipated concept. The SAFIN&L format was examined by two chemistry educators in regards to the appropriateness of the removed concepts and relations and the determinability of the gaps created. The authors had two fourth-year students who had previous experience with concept maps check the SAFIN&L map it terms of its understandability. The final version of the SAFIN&L is shown in Appendix V.
3.1.2.3. The reliability of the concept maps. As part of the pilot study, all four different fill-in-the-blank concept maps were administered to 30 chemistry students at different times in order to determine their reliability. In other words, each map type was tested by 30 participants.

The correct/wrong answers were scored on a 1/0 basis. Since the internal consistency coefficient determined by KR-20 came out to be almost the same as that determined by Cronbach's alpha (Bademci, 2011), the alpha coefficient for each type of map was separately calculated using SPSS 15 statistical software. These values, calculated for all 30 participants, are listed in Table 4. Based on these α values, the concept maps developed in this study were considered to be reliable data collection tools.

Table 4 The internal consistency coefficients of the fill-in-the-blank maps
Map type Alpha (α)
Select and fill in the nodes SAFIN 0.957
Create and fill in the lines CAFIL 0.953
Select and fill in the lines SAFIL 0.942
Select and fill in the nodes&lines SAFIN&L 0.966

3.2. Participants

The study included three sample groups. The first phase of the pilot study was conducted with the first group (N = 148), while the second phase was carried out with the second group (N = 30). The main application was carried out with the third group (N = 19).

All students were informed that they are participating in a research, the data might be used for in published reports and they could leave work at any time without prejudice.

3.2.1. Participants of the pilot study. In the first stage of the pilot study involving 148 undergraduates, the validity and reliability analysis of the concept test was completed. Among these 148 students, 81 were studying in the Chemistry Department of the Education Faculty, 25 in the Chemistry Department of the Science Faculty and 42 in the Pharmacy Department. Students from other faculties who were taking an analytical chemistry course with similar content were included in the study to increase the sample size.

In the second stage of the pilot study, the preparation of the fill-in-the-blanks concept maps and the validity and reliability analysis of these maps were completed. A total of 30 chemistry students (25 females and 5 males) studying in their second year at a state university were included in this pilot study. The participants in the second phase were different from those involved in the first stage. At this stage, the participants received training on concept mapping that would be applied in the main study.

3.2.2. Participants of the main study. The main study included 19 chemistry students (13 females and 6 males) who were in their second year at a state university and taking an analytical chemistry course. Since this study was conducted on gravimetric analysis, participants were required to be currently enrolled in an analytical chemistry course.

All participants were briefed on concept maps before performing the study.

This study used the multi-purpose sampling method, which perfectly aligns with qualitative research principles. According to Patton (1987), the random sampling method has high expressive power for making valid generalizations about the universe, while the purposive sampling method is better suited for in-depth investigations of a certain case or for obtaining very rich data for certain circumstances.

3.3. Selection of the subject matter

Gravimetric analysis, a topic addressed as part of Analytical Chemistry courses, involves explaining the theory of gravimetric methods. The basic reason for selecting this course was that despite the highly calculus-related nature of analytical chemistry, the topic of gravimetric analysis contains nearly 40 concepts, with numerous relations between them. It is clear that teaching such a large number of concepts and conceptual relations to achieve meaningful learning using the expository method would be very difficult, if not impossible. Therefore, it was believed that the concept mapping method, which enables the students to relate the concepts in a visual way, would remedy this problem. Although gravimetric analysis includes so many concepts, results from the literature review showed there to be no studies related to the teaching of this topic.

3.4. Research design

In this study, a case study research design was used to quantitatively examine the effect of the use of concept mapping as an individual learning tool on the success of chemistry students to conceptualize. In addition, a detailed qualitative investigation was performed on the opinions of the chemistry students about its use. Case studies are a type of research method that gathers detailed information about a special case using qualitative and quantitative methods (Patton, 2002) to reveal the contents of a complex situation (Taber, 2007). This study was designed as a case study because the sample was small enough to perform a quantitative and qualitative in-depth study of a specific case. The hypothesis developed for this study was that learners do not meaningfully learn the concepts about gravimetric analysis when traditional methods of learning are used.

McClure et al. (1999) defined the possible source errors in measurements involving concept maps as follows: (1) differences between the levels of familiarity students have with concept maps (2) differences between the content knowledge levels of the assessors (in cases where there are more than one assessors for the assessment process), and (3) consistency in the concept map grading. The participants were chosen from among a selection of students who had no previous experience with concept maps to ensure uniformity of the research group.

3.5. Main study

The study was carried out with the participation of 2nd-year students studying in the chemistry education department of a state university.

In this study, concept maps were used both as a data collection tool (SAFIN, CAFIL, SAFIL and SAFIN&L) and as an individual learning tool (concept maps created by the students from scratch). The participants were first briefed on gravimetric analysis by the lecturer of the course using the conventional expository method. The participants then completed, as pre-tests (concept maps as data collection tools) the GCT, SAFIN, CAFIL, SAFIL and SAFIN&L, in respective order, on different days. All map types were applied to all 19 students. The participants were not pre-informed about the fact that the same concept map was applied in four different formats in order to prevent the participants from memorizing the concepts and the relations, which would jeopardize the scoring of the map. Next, the participants prepared 3 concept maps about the gravimetric analysis on their own. This stage took 3 weeks (two hours a week). During this stage, the participants continued to receive training in other analytical chemistry topics not directly connected with the gravimetric analysis.

Concept mapping is a learning process whereby students can benefit from greater feedback and scaffolding to support their learning (Pudelko et al., 2012). Since the effect of concept mapping as an individual learning tool on the success of the participants’ ability to learn the concepts associated with gravimetric analysis has been studied, the participants were allowed to use any source of documents (internet or notes about gravimetric analysis) when creating the concept map from scratch at this stage. In this way, the students had the opportunity to re-examine the concepts that they realized were missing when they were creating the concept map.

At the end of this stage, the participants once again completed the GCT, SAFIN, CAFIL, SAFIL and SAFIN&L as post-tests. Also, the opinions of the participants on the use of concept maps as an individual learning tool were taken using written concept mapping opinion forms. Based on the analysis of these opinion forms, some of the participants were selected to be interviewed.

3.5.1. The preparation process for the concept maps.
1st stage: introduction of the concept maps. In the first two hours, the participants were briefed on the theory, objectives and application of the concept maps. The components of the concept maps were thoroughly explained, and examples of correct and incorrect formats were given. The participants were provided examples of well-organized and badly-organized maps, instructed on the importance of the structure of the concept maps, and given detailed information about Novak, Fill-in-the-blank and Indexing methods (Turan-Oluk and Ekmekci, 2016a) from among the concept map preparation methods. Concept maps drawn in accordance to each method were presented. For example, a concept map involving 16 concepts on the simple topic of “matter” would be presented according to the indexing method. Any questions the students had with regard to the method were noted and immediately addressed.
2nd stage: preparation of a concept map in groups. In the second stage of the process, the participants, in groups of two, were asked to establish a concept map related to the subject of “atom” by using 19 of the relevant concepts. The participants were placed at a round table, where they were allowed to discuss the matter among themselves and perform the map preparing stages. The researcher was careful to personally sort out any of the problems experienced by the participants who were having difficulties.
3rd stage: application. In the application stage, the participants prepared 3 concept maps on gravimetric analysis. The concepts necessary to prepare the maps were provided by the researcher.

The participants were given the 14 concepts shown in the first column of Table 5 and were asked to create a concept map from scratch. The maps prepared by the participants were assessed in terms of their conceptional content and map components and then returned back to them after all the errors or flaws were clearly marked. In addition to the first 14 concepts, 14 more concepts were given to the participants for the second concept map, bringing the total number of concepts to 28 concepts (see Table 5). The participants made the necessary corrections on their second maps according to the feedback they received on the first ones. The second maps were also subjected to a thorough check for conceptual content and components, and any mistakes or flaws on the map were marked before returning them to the participants. Finally, the participants were given 11 new concepts (see Table 5) for the third map, in addition to those already given for the first two maps, bringing the total to 39 concepts for the final and most complicated map. Careful attention was given to increasing the number of concepts from the first map to the third map in a hierarchical manner.

Table 5 The concepts that were used to create the concept maps
image file: c8rp00079d-u1.tif

3.6. Data collection tools and data analysis

There were 25 questions on the gravimetric analysis concept test. Each correct answer was scored four points, with the total possible points being 100.

The concept maps were scored according to the scoring system devised by Novak and Gowin (1984). With this system, each correct concept is scored 1 point, each correct proposition, 1 point, each correct and important cross link, 10 points, cross links of secondary importance, 2 points and each hierarchical level, 5 points. The hierarchy was predetermined and given to the participants, therefore it was not included in the scoring system.

The fill-in-the-blank concept maps were scored based on the master map prepared. The select-and-fill-in-the-nodes concept map included 37 concept gaps. The participants were asked to choose the most suitable concept from a list of 50 concepts that included 13 misleading ones. The 37 gaps in the maps were marked as true or false on the basis of the master map. The maximum points possible on this map were 37. The points scored by the participants on this test were converted into decimal form in order to compare the points scored against the other maps.

There were two different fill-in-the-line map types employed in the study, namely, the Create-and-fill-in-the-lines (CAFIL) and the Select-and-fill-in-the-lines (SAFIL). In CAFIL, the participants were asked to construct the relations by themselves. The maps were scored according to how well the proposals and cross-lines matched with the master map. In SAFIL, the participants were asked to choose the most appropriate relation from the list containing 50 relations, 11 of which were misleading. Among the 41 relation gaps, 11 were cross linked, and 2 of these cross-linked relations were of secondary importance. The maximum points possible on this map were 124. The points scored by the participants on this map were also converted into decimal form. As an example, the total points of a student who filled in 36 gaps (five cross-links with one of secondary importance) correct would be calculated as ((30 × 1) + (1 × 2) + (5 × 10))/124 × 100 = 66.13, which would be rounded to 66.

In the partially-filled map there were 19 concepts and 19 relation gaps (9 cross-links, 1 of secondary importance), and a maximum possible points of 111.

The participants’ opinions on the usability of the concept maps as an individual learning tool were determined with “The Attitude Scale for Concept Mapping” (Turan-Oluk et al., 2016b) and with a three-question survey, titled “The Opinions about Concept Mapping”, developed by the author.

The items of the Attitude Scale for Concept Mapping (which includes 23 items in its original form) related to the use of concept maps as a teaching or learning tool were analyzed (Table 6) to determine their frequencies.

Table 6 The items for the concept maps as a teaching/learning method
Item no. Items
1 I think that I understood the topic after preparing the concept map.
4 Concept maps helped me to learn the key concepts.
5 Concept maps directed me to individual thinking.
6 Concept maps improved my thinking system.
9 Concept maps facilitated establishment of relations between the concepts.
11 Concept maps helped me to improve my knowledge on the course content.
16 Concept maps showed me how I understood the topic.

“The Opinions about Concept Mapping” survey included the three questions listed below to discover the opinions of the participants on the effect of the use of concept maps on their success in conceptually understanding gravimetric analysis as an individual learning tool.

(1) Is the preparation of concept maps on gravimetric analysis helpful for learning the topic? Explain

(2) Do you think there are any differences between your knowledge of gravimetric analysis following the exposition process versus the knowledge gained after the preparation of the concept map? Explain.

(3) What do you think about the use of concept maps as a learning tool? Explain.

The written responses given by the participants to “The Opinions about Concept Mapping” survey were subjected to content analysis. With content analysis, any raw data similar to each other are compiled under certain themes, which are then presented as main categories (Strauss and Corbin, 1990).

Furthermore, the effect size, which is used to measure the magnitude of the method employed, or the size of difference between mean values, was determined (Fraenkel and Wallen, 2006). Effect size is usually reported as a standardized difference or a standardized amount of shared variability (Beins and McCarthy, 2012). In the statistical analysis, the effect size, which shows the size of the difference between the mean values of two groups, was computed with Cohen's d formula, the most widely used formula for this purpose (Ozsoy and Ozsoy, 2013). With this formula, d ≤ 0.20 corresponds to small, 0.20 < d < 0.80 to medium and d ≥ 0.80 to a large effect size (Cohen, 1988). Moreover, the APA (2010) suggests that effect size be reported because it provides important information about the applicability of the differences between means.

3.7. Validity and reliability of the study

The internal consistency of the study was established via data triangulation. The change in the participants’ success in understanding the concepts was determined using five different data collection tools, the GCT, SAFIN, CAFIL, SAFIL and SAFIN&L. The reliability of the study was verified by a detailed descriptive model. Finally, the validity and reliability values of all the data collection methods were explained in detail to verify their validities and reliabilities.

4. Results

From the results of this study, it is clear that the concept maps can be used as both a teaching/learning method and an assessment tool. The concept maps were used as a learning tool to determine their effect on the success of the participants to understand concepts as well as an assessment tool to determine the extent of the change. The fact that the participants had to fill in four different concept maps consecutively may have imposed a distortive effect upon the study. To test for this effect, the pre-test concept map points scored by the participants were plotted in accordance to the order of the application (1-SAFIN, 2-CAFIL, 3-SAFIL, 4-SAFIN&L), and the findings showed no linearity in the resulting plot (Fig. 1).
image file: c8rp00079d-f1.tif
Fig. 1 The pre-test concept map points scored by the participants.

As seen from the plot, the concept test points scored by the participants did not show a linear change from the first map to the last. Based on this data, it can confidently be claimed that the change in the success took place only during the individual concept maps learning period.

The normal distribution condition is examined by Shapiro–Wilks test when the group size is smaller than 50 and by the Kolmogorov–Smirnov test when the group size is bigger than 50 (Joaquim, 2007). Since the present study was carried out with 19 students, Shapiro–Wilks test was used for determining whether or not the points showed a normal distribution. Table 7 shows the normal distribution data.

Table 7 The normal distribution values belonging to the points scored
Test name [X with combining macron] S p
a The values show normal distribution (N = 19).
GCTprea 64.00 11.15 0.224
GCTposta 73.68 11.79 0.398
SAFINprea 41.00 18.30 0.538
SAFINpost 74.95 21.05 0.014
CAFIL pre 31.74 23.73 0.023
CAFIL posta 52.74 24.14 0.369
SAFIL prea 35.89 24.68 0.313
SAFIL posta 57.21 23.09 0.491
SAFIN&L prea 36.10 20.98 0.107
SAFIN&L posta 45.68 19.43 0.095

The significance of the difference between the points showing a normal distribution was determined by the t-test, while the significance between the points not showing a normal distribution were investigated by Wilcoxon labeled rank test. Table 8 shows the t-test results and Table 9 gives the Wilcoxon labeled rank test results.

Table 8 t-Test results
[X with combining macron] S sd t p
a 1: pre test, 2: post test; N = 19.
GCT 1a 64.00 11.15 18 −3.723 0.002
2 73.68 11.80
SAFIL 1 35.89 24.68 18 −6.62 0.000
2 57.21 23.09
SAFIN&L 1 36.10 20.98 18 −2.91 0.009
2 45.68 19.43

Table 9 Wilcoxon labeled rank test
Post test–pre test Mean rank Sum of ranks z p
a Based on negative ranks, N = 19.
SAFIN Negative ranks 0.00 0.00 −3.825a 0.000
Positive ranks 10.00 190.00
Ties — —
CAFIL Negative ranks 2.00 2.00 −3.743 0.000
Positive ranks 10.44 188.00
Ties —

As can be seen from Table 8, there was a significant increase in the conceptual test points of the participants on gravimetric analysis when they used the concept maps as an individual learning tool (t(18) = −3.723, p < 0.05). The mean points scored by the participants on the pre-test taken prior to the study of the concept maps was [X with combining macron] = 64.00. This value increased to [X with combining macron] = 73.68 when the conceptual post-tests were applied after the study of the concept maps. Similarly, there were statistically significant point increases by the participants from the SAFIL and SAFIN&L pre-test to the post-test (t(18) = −6.62, p < 0.05; t(18) = −2.91, p < 0.05).

According to the Wilcoxon labeled rank test results (see Table 9), the use of concept maps as a learning tool for gravimetric analysis resulted in a significant difference between pre-test and post-test scores (z = −3.825, p < 0.01; z = −3.743, p < 0.01). When looking at the rank averages and totals, the difference was found to be in favor of the positive ranks for the post-test results.

There were significant differences between the participants’ pre-test and post-test scores for GCT, SAFIN, CAFIL, SAFIL, SAFIN&L (Tables 8 and 9). According to these results, it can be said that the use of concept maps as a personal learning tool has a synergistic effect upon the success in understanding the concepts of gravimetric analysis.

The size, or practical meaning, of this effect was determined to be: d = 0.87 for GCT; d = 1.77 for SAFIN; d = 0.90 for CAFIL; d = 0.92 for SAFIL and d = 0.49 for SAFIN&L. These values indicate that the effect size was highly significant.

In analyzing the items related to the effect of the concept maps, most of the participants marked the choices of “strongly agree” or “agree”. Fig. 2 shows the frequencies of the responses of the participants. When Table 6 and Fig. 2 are evaluated together it comes out that the use of the concept maps has a synergistic effect upon the learning process. Considering the participants’ opinions on the use of concept maps, it can be seen that all of them stated that the use of concept maps had a positive effect upon their learning process. Here are some excerpts from their opinions.


image file: c8rp00079d-f2.tif
Fig. 2 Lists the responses to attitude scale for concept mapping.

No matter how well one thinks that he/she fully understood the topic there remains a few unclarified points. The concept maps helped me to solidify my knowledge and to advance my knowledge on certain subjects by establishing the relations between the relevant concepts (Mary)

Concept maps helped me to learn the gravimetric analysis, enabling me to see the relation between the concepts (William).

Concept maps should be widely used as a learning/teaching method in courses such as chemistry, where the concepts are strongly related to each other. It enables us to see the topic in a more integrated manner, which allows us to see the relations between the concepts much more easily (Susan).

I realized that I learned something about gravimetric analysis after the preparation of the concept maps. I think that it is a non-rote based method with good educative power (Jennifer).

I would always try to memorize the concepts for topics that included so many of them. I was unable to establish any ties between them. I was not learning; I was memorizing. But after the establishment of a concept map, I realized that I was not memorizing the concepts of gravimetric analysis any more. I was learning them (Anna).

The lectures given in an expository manner do have a permanent effect on me. However, when I prepared a concept map, I think that I learned gravimetric analysis in a much more effective way (Alice).

5. Discussion

Concept mapping is an effective learning strategy for providing meaningful learning (Novak et al., 1983). It allows the student to add any new information and facts to the existing information schema by establishing a connection with the prior information, and to change the schema when it is not possible (Novak and Gowin, 1984). Concept mapping can be defined in simple terms as learning via creation of a concept map (Altınok, 2004).

The study revealed significant differences between the pre-test and post-test values on all the tests employed, in favor of the post-test grades. Considering that the pre-tests were applied after the presentation of the gravimetric analysis by a conventional method, it can be said that the increase in success, from pre-test to post-test was due to the concept mapping process. In other words, the successes of the students in gravimetric analysis increased when they used concept maps as an individual learning tool. As a learning tool, concept maps help the students to see the relations between the different parts of the subject (Novak, 1990; Schwendimann, 2016). In fact, when a person creates a concept map, they have the opportunity to see connections and relationships that they had not previously understood. This allows the person to review the concepts they do not understand and thereby improve their learning. Since the features of a concept map and its many learning aids, such as orientation to active learning and summary of the topic, help concepts to be organized in the mind by establishing relationships between concepts and facilitate remembering, concept maps can be thought to contribute to the increase of students' success in conceptual understanding. Concept maps are able to positively influence conceptual understanding success by providing a holistic view of the subject (Çömek et al., 2016; Turan-Oluk, 2016).

According to Novak and Gowin (1984), concept maps present an important part of the topics in a systematic manner and make the key concepts much more understandable for the students. Also, Çömek et al. (2016), Erdem et al. (2009), Sarıca and Çetin (2012), Šket et al. (2015) and Qarareh (2010) reported that concept maps promoted success in conceptual understanding. Similarly, Greene et al. (2013) found that the use of concept maps resulted in a significant difference between the pre- and post-test values in all types of tests, and stated that it was an effective way to enlighten students’ conceptual structure. Lin et al. (2016) stated that regardless of whether concept maps were prepared by hand or generated via computer media they have a very positive effect on success in conceptual understanding. It was further observed that the use of concept maps as a learning method increased understanding of gravimetric analysis to quite a large extent.

As is the case for all studies, the meaning of the statistical data related to the education field is of the utmost importance. One can talk about two meanings: statistical meaning and practical meaning (Ozsoy and Ozsoy, 2013). The high effect size found in this study was an indication that the use of concept maps definitely had a synergistic effect on the perception of gravimetric analysis. Batdi (2014) in his meta-analysis study investigating the effect of concept maps on 40 people, found the effect size of the concept maps to be 1.0696 for social sciences subjects and 0.936 for hard science subjects.

Similarly, Horton et al. (1993), in his meta-analysis, found that concept mapping had positive effects on both student success and attitudes in the 18 studies examined. Martínez et al. (2013), in their study of concept maps on two different science topics, reported high effect sizes (d = 0.842 and d = 0.778). All these results serve to indicate that the concept maps have an undeniable positive effect upon conceptual understanding success. Chemistry concepts, in contrast to daily concepts, are generally more abstract and much more difficult to learn (Taber, 2002). Considering these conceptual difficulties related to certain subjects, the proven significant effect of concept maps on conceptual understanding success merits serious attention.

According to Schau et al. (2001), the provision of a list of relations in gap concept maps makes them more complicated, as the relations given are general statements that may fit into any gap. This causes more stress on the students. Yin et al. (2005) reported that students spent much more time and effort on the relation-gap concept maps when they had the list of relations provided compared to the when they had maps where they were supposed to write down the answer by themselves. Moreover, the same researchers stated that create-form and select-form maps had similar standard deviations and similar correlations with the multiple-choice tests. In this study, contrary to the literature, the select-form yielded higher mean points. As discovered from the discussion with the participants, this was attributed to the higher association related to the concepts when the participants are given a statements list.

The participants expressed very positive opinions about the concept maps on both the attitude scale and their written opinions, claiming that it definitely had a successful effect on conceptual understanding. Jaafarpour et al. (2016) reported that the participants in their study regarded concept maps as a good learning tool and as an educational strategy that promoted meaningful learning. Taber (2002) also notes that students can use concept maps to test their knowledge and use them as an effective technique for evaluating their own development. Although the participants were very pleased with the concept maps as a learning tool, they did complain about its time-consuming nature. The preparation of fill-in-the-blank type concept maps serves to mitigate the inherent time-consumption problem related to concept mapping and to make the concept maps much more usable.

6. Conclusions

Although pre-tests were applied immediately after administering a traditional method of teaching gravimetric analysis, the low pre-test scores indicate that the traditional method was not sufficiently effective. However, the fact that the final test scores from the three self-concept maps applied on this subject were high, with a significant difference between the pre-tests and the final tests, shows how highly effective the study of the concept map was. In the process of preparing the concept map, students apprehended the missing concepts and inter-concept relationships, which led them to reconsider the issue, and as a result, there was a significant increase in their success. From these results, it can be said that concept maps are an effective tool for directing students study in such a way as to increase their success.

Based on the opinions taken from the participants, the following conclusions can be made.

(1) The concept map makes it possible to identify points that are not understood.

(2) The concept map allows the subject to be seen as a whole.

(3) The concept map allows meaningful learning to occur, instead of memorization.

The participants’ views that the concept map had a positive impact on learning, the improvement in their success at understanding concepts, as demonstrated by the increased scores from the pre-test to the post-test, and the high effect size, all serve to prove that concept maps have a positive effect on strengthening learning.

Implications

The fill-in-the-blank concept maps related to the concepts associated with gravimetric analysis can be used as summative evaluation tools. This method has major advantages, even for those who have never taken a course on how to prepare concept maps. As assessment tools, concept maps are able to evaluate the performance of students in a much shorter time compared to conventional assessment tools, and are equally as quick and easy as classical true/false tests. On the learning side, one of the main advantages of concept maps is their ability to display and organize conceptual relations in a visual manner.

The validity and reliability studies revealed that the fill-in-the-blank type concept maps developed for the gravimetric analysis could be useful as a data collection tool for researchers working in this field of study. The fill-in-the-blank type concept maps are believed to be a highly effective teaching/learning tool for chemistry topics that have a high number of concepts. Lastly, this study can serve as an example for developing concept maps in other chemistry topics.

Conflicts of interest

There are no conflicts to declare.

Appendix I: gravimetric analysis concept test

1. Which quantitative parameter is measured in gravimetric analysis?

(a) Volume (b) Mass (c) Molarity (d) Mol number (e) Molar mass

2. Which of the following is a gravimetric analysis method?

(I) Precipitation Gravimetry

(II) Volatilization Gravimetry

(III) Electrogravimetry

(IV) Volumetric Gravimetry

(a) I and II (b) I and III (c) II, III and IV

(d) I, II, III and IV (e) I, II and III

3. Why is the precipitate is washed with pure water or electrolyte?

(a) To provide nucleation

(b) Increase the relative over saturation

(c) Purify from impurities

(d) Ensuring the maturation

(e) Enable the co precipitation

4. Fill the blanks with the most appropriate concepts in the following text.

The …I… of the solids formed by precipitation varies in a wide range. At one end of the space there is a …II… whose particles are not visible to the naked eye which are not prone to precipitation in the solution. At the other end of this range there is large particular …III… which is readily precipitated and easily filtered.

image file: c8rp00079d-u2.tif

5. Which of the following procedures decrease the relative over saturation?

(I) Rapid addition of the reactant

(II) Increasing the temperature

(III) Rigorous mixing of the solution

(IV) Increasing the molarity of the solution

(a) I and II (b) II and III (c) III and IV

(d) I, II and III (e) II, III and IV

6. Which of the following is NOT a co-precipitation process?

(a) Surface adsorption

(b) Nucleation

(c) Mechanical entrapment

(d) Occlusion

(e) Mixed crystal formation

Answer questions of 7, 8, 9 and 10 according to the following text.

In the precipitation gravimetry, the substance to be analyzed is precipitated as a …7… precipitate. This precipitate is then …8…with electrolyte and the …9…that may be present are removed. The compound is then subjected to a suitable heat treatment to convert it a…10… with a known composition.

7. (a) Insoluble (b) Slightly soluble (c) Very soluble

(d) Colloidal soluble (e) Crystalline soluble

8. (a) Washed (b) Dried (c) Filtered

(d) Centrifuged (e) Kept

9. (a) Impurity (b) Analyte (c) Precipitated mass

(d) Solvent (e) Crystalline suspension

10. (a) Efficiency (b) Reactant (c) Impurity (contamination)

(d) Product (e) Input

image file: c8rp00079d-u3.tif

Appendix II: gravimetric analysis concept map (master map)


image file: c8rp00079d-u4.tif

Appendix III: gravimetric analysis concept map (select and fill in the nodes (SAFIN))


image file: c8rp00079d-u5.tif

Appendix IV: gravimetric analysis concept map (select and fill in the lines (SAFIL) and create and fill in the lines (CAFIL))


image file: c8rp00079d-u6.tif

Appendix V: gravimetric analysis concept map (select and fill in the nodes&lines (SAFIN&L))


image file: c8rp00079d-u7.tif

References

  1. APA, American Psychological Association, (2010), Publication manual of the American Psychological Association, 6th edn, Washington, DC: Author.
  2. Altınok H., (2004), Cooparative learning, concept mapping, science achievement strategy use and attitude, Unpublished doctoral dissertation, Dokuz Eylül University, İzmir, Turkey.
  3. Atılgan H., (2009), Test geliştirme, in Atılgan H. (ed.), Eğitimde ölçme ve değerlendirme, 4th edn, Ankara: Anı, pp. 315–348.
  4. Ayas A., (2005), Kavram öğrenimi, in Çepni S. (ed.), Kuramdan uygulamaya fen ve teknoloji öğretimi, Ankara: Pegem, pp. 65–91.
  5. Bademci V., (2011), A Study on the Kuder-Richardson 20, Cronbach's Alpha, Hoyt's Analysis of Variance, Generali-zability Theory and Score Reliability, Dicle University Journal of Ziya Gökalp Faculty of Education, 17, 173–193.
  6. Batdi V., (2014), The effect of using the concept-mapping technique and traditional methods on the achievement, retention and attitudes of students: a meta-analytic study, Dumlupinar University Journal of Social Science, 42, 93–102.
  7. Beins B. C. and McCarthy M. A., (2012), Research Methods and Statistics, New York: Pearson.
  8. BouJaoude S. and Attieh M., (2008), The effect of using concept maps as study tools on achievement in chemistry, Eurasia J. Math., Sci. Technol. Educ., 4(3), 233–246.
  9. BouJaoude S. and Barakat H., (2000), Secondary school students' difficulties with stoichiometry, Sch. Sci. Rev., 81(296), 91–98.
  10. Cohen J., (1988), Statistical power analysis for the behavioral sciences, 2nd edn, Hillsdale, NJ: Lawrence Earlbaum Associates.
  11. Çömek A., Akınoğlu O., Elmacı E. and Gündoğdu T., (2016), The effect of concept mapping on students’ academic achievement and attitude in science education, J. Hum. Sci., 13(1), 348–363.
  12. Conradty C. and Bogner F. X., (2010), Implementation of concept mapping to novices: reasons for errors, a matter of technique or content? Educ. Stud., 36(1), 47–58.
  13. Didiş N., Özcan Ö. and Azar A., (2014), What do pre-service physics teachers know and think about concept mapping? Eurasia J. Math., Sci. Technol. Educ., 10(2), 77–87.
  14. Ebenezer J. V., (1992), Making chemistry learning more meaningful, J. Chem. Educ., 69(2), 464–467.
  15. Erdem E., Yılmaz A. and Oskay Ö. Ö., (2009), The effect of concept mapping on meaningful learning of atom and bonding, Procedia-Soc. Behav. Sci., 1(1), 1586–1590.
  16. Fraenkel J. R. and Wallen N. E., (2006), How to design and evaluate research in education, 6th edn, New York: McGraw-Hill Companies.
  17. Fraser K. and Edwards J., (1985), The effects of training in concept mapping on student achievement in traditional classroom tests, Res. Sci. Educ., 15, 158–165 DOI:10.1007/ BF02356538.
  18. Gabel D., (1999), Improving teaching and learning through chemistry education research: a look to the future, J. Chem. Educ., 76(4), 548–554.
  19. Greene B. A., Lubin I. A., Slater J. L. and Walden S. E., (2013), Mapping changes in science teachers’ content knowledge: concept maps and authentic professional development, J. Sci. Educ. Technol., 22(3), 287–299.
  20. Gul R. B. and Boman J. A., (2006), Concept mapping: a strategy for teaching and evaluation in nursing education, Nurse Educ. Pract., 6(4), 199–206.
  21. Horton P. B., McConney A. A., Gallo M., Woods A. L., Senn G. J. and Hamelin D., (1993), An Investigation of the effectiveness of concept mapping as an instructional tool, Sci. Educ., 77(1), 95–111.
  22. Jaafarpour M., Aazami S. and Mozafari M., (2016), Does concept mapping enhance learning outcome of nursing students? Nurse Educ. Today, 36, 129–132.
  23. Joaquim M., (2007), Applied statistics using SPSS, STATISTICAL, MATLAB, and R, 2nd edn, New York: Springer.
  24. Kan A., (2009), Ölçme araçlarında bulunması gereken nitelikler, in Atılgan H. (ed.), Eğitimde Ölçme ve Değerlendirme, 4th edn, Ankara: Anı, pp. 23–80.
  25. Kurada K., (2006), The effect of concept maps on learning history lesson for 10th grades, İstanbul: Marmara University Institute of Educational Sciences, Master Thesis.
  26. Lin Y. T., Chang C. H., Hou H. T. and Wu K. C., (2016), Exploring the effects of employing Google Docs in collaborative concept mapping on achievement, concept representation, and attitudes, Interact. Learn. Environ., 24(7), 1552–1573.
  27. Markow P. G. and Lonning R. A., (1998), Usefulness of concept maps in college chemistry laboratories: students’ perceptions and effects on achievement, J. Res. Sci. Teach., 35(9), 1015–1029.
  28. Martínez G., Pérez Á. L., Suero M. I. and Pardo P. J., (2013), The effectiveness of concept maps in teaching physics concepts applied to engineering education: experimental comparison of the amount of learning achieved with and without concept maps, J. Sci. Educ. Technol., 22, 204–214 DOI:10.1007/s10956-012-9386-8.
  29. Martínez G., Mateos M. and Naranjo F. L., (2016), Design and validation of a teaching sequence based on concept maps to achieve meaningful learning of science content in primary education, in Cañas A. J., Reiska P. and Novak J. D. (ed.), Innovating with Concept Mapping. Proceedings of the Seventh International Conference on Concept Mapping, Switzerland: Springer International Publishing, vol. 1, pp. 54–65.
  30. McClure J. R., Sonak B. and Suen H. K., (1999), Concept map assessment of classroom learning: reliability, validity, and logistical practicality, J. Res. Sci. Teach., 36(4), 475–492.
  31. Mintzes J. J., Wandersee J. H. and Novak J. D., (2000), Assessing science understanding: a human constructivist view, San Diego, CA: Academic Press.
  32. Moon B., Hoffman R. R., Novak J. and Cañas A. (ed.), (2011), Applied concept mapping: capturing, analyzing, and organizing knowledge, USA: CRC Press.
  33. Nakhleh M., (1992), Why some students don't learn chemistry: chemical misconceptions, J. Chem. Educ., 69(3), 191–196.
  34. Novak J. D. and Cañas A. J., (2006), The theory underlying concept maps and how to construct and use them, Technical Report IHMC CmapTools 2006-01 Rev 01-2008, Florida Institute for Human and Machine Cognition.
  35. Novak J. D. and Gowin D. B., (1984), Learning how to learn, New York: Cambridge University Press.
  36. Novak J. D. and Musonda D., (1991), A twelve-year longitudinal study of science concept learning, Am. Educ. Res. J., 28(1), 117–153.
  37. Novak J. D., (1990), Concept maps and vee diagrams: two metacognitive tools to facilitate meaningful learning, Instruct. Sci., 19, 29–52.
  38. Novak J. D., (1998), Learning, creating and using knowledge: concept maps as facilitative tools in schools and corporations, Mahwah, NJ: Lawrence Erlbaum Associates.
  39. Novak J. D., Gowin D. B. and Johansen G. T., (1983), The use of concept mapping and knowledge vee mapping with junior high school science students, Sci. Educ., 67(5), 625–645.
  40. Osterlind S. J., (2002), Constructing test items: multiple-choice, constructed-response, performance, and other formats, 2nd edn, Boston: Kluwer Academic Publishers.
  41. Ozsoy S. and Ozsoy G., (2013), Effect size reporting in educational research, Elementary Education Online, 12(2), 334–346.
  42. Patton M., (1987), How to use qualitative methods in evaluation, London: Sage Publications.
  43. Patton M. Q., (2002), Qualitative research and evaluation methods, 3rd edn, Thousand Oaks, CA: Sage.
  44. Pudelko B., Young M., Vincent-Lamarre P. and Charlin B., (2012), Mapping as a learning strategy in health professions education: a critical analysis, Med. Educ., 46(12), 1215–1225.
  45. Qarareh A. O., (2010), The effect of using concept mapping in teaching on the achievement of fifth graders in science, Stud Home CommSci, 4(3), 155–160.
  46. Ruiz-Primo M. A. and Shavelson R. J., (1996), Problems and issues in the use of concept maps in science assessment, J. Res. Sci. Teach., 33(6), 569–600.
  47. Ruiz-Primo M. A., Schultz S. E., Li M. and Shavelson R. J., (2001a), Comparison of the reliability and validity of scores from two concept-mapping techniques, J. Res. Sci. Teach., 38(2), 260–278.
  48. Ruiz-Primo M. A., Shavelson R. J., Li M. and Schultz S. E., (2001b), On the validity of cognitive interpretations of scores from alternative concept-mapping techniques, Educ. Assess., 7(2), 99–141.
  49. Safayeni F., Derbentseva N. and Cañas A. J., (2005), A theoretical note on concepts and the need for cyclic concept maps, J. Res. Sci. Teach., 42(7), 741–766.
  50. Sarıca R. and Çetin B., (2012), The effects of using concept maps on achievement and retention in teaching science lessons, Elementary Education Online, 11(2), 306–318.
  51. Schau C., Mattern N., Zeilik M., Teague K. W. and Weber R. J., (2001), Select-and-fill-in concept map scores as a measure of students’ connected understanding of science, Educ. Psychol. Meas., 61(1), 136–158.
  52. Schwendimann B. A., (2016), Critiquing as an alternative to generating concept maps to support knowledge ıntegration processes, in Cañas A. J., Reiskaand P. and Novak J. D. (ed.), Innovating with Concept Mapping. Proceedings of the Seventh International Conference on Concept Mapping, Switzerland: Springer International Publishing, vol. 1, pp. 40–53.
  53. Seel N. M., (2012), Assimilation theory of learning, Encyclopedia of the Sciences of Learning, Springer US, pp. 324–326.
  54. Sisovic D. and Bojovic S., (2000), On the use of concept maps at different stages of chemistry teaching, Chem. Educ. Res. Pract., 1(1), 135–144.
  55. Šket B., Glažar S. A. and Vogrinc J., (2015), Concept maps as a tool for teaching organic chemical reactions, Acta Chim. Slov., 62(2), 462–472.
  56. Sözbilir M. and Neacşu I. (ed.), (2014), Alternative assessment and evaluation methods: a practical guide book for teachers, Erzurum/Bucharest: Erzurum Provincial Directorate of National Education.
  57. Stensvold M. and Wilson J. T., (1992), Using concept maps as a tool to apply Chemistry concepts to laboratory activities, J. Chem. Educ., 69(3), 230.
  58. Strauss A. L. and Corbin J., (1990), Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Newbury Park, CA: Sage.
  59. Taber K. S., (2002), Chemical misconceptions –prevention, diagnosis and cure: Theoretical background, London: Royal Society of Chemistry, vol. 1.
  60. Taber K. S., (2007), Classroom-based research and evidence-based practice: a guide for teachers, London: SAGE.
  61. Turan-Oluk, (2016), The comparison of different concept mapping tasks in chemistry education, Unpublished doctoral dissertation, Ankara, Turkey: Gazi University.
  62. Turan-Oluk N. and Ekmekci G., (2016a), A different approach to preparing novakian concept maps: the indexing method, Educ. Sci.: Theor. Pract., 16(6), 2111–2140.
  63. Turan-Oluk N., Kan A. and Ekmekci G., (2016b). Kavram haritasi yöntemine yönelik tutum ölçeğinin geliştirilmesi: geçerlik ve güvenirlik çalişmasi, Journal of Kirsehir Education Faculty, 17(1), 95–110.
  64. Yin Y., Vanides J., Ruiz-Primo M. A., Ayala C. C. and Shavelson R. J., (2005), Comparison of two concept-mapping techniques: implications for scoring, interpretation, and use, J. Res. Sci. Teach., 42(2) 166–184.
This journal is © The Royal Society of Chemistry 2018