Data collection outside and inside the classroom: Personal Meaning Mapping Anthony Lelliott Marang Centre for Maths and Science Education, School of Education, University of the Witwatersrand, Johannesburg email: anthony.lelliott@wits.ac.za Abstract This paper describes how Personal Meaning Maps, a variant of concept maps can be used to gather data from individuals on their thinking around a topic in science education. Using examples from a research study examining student learning when visiting an astronomy science centre, this paper explores the theory behind the practice of PMM, how it is conducted, how it can be analyzed, and its possible uses in research and teaching. Introduction Personal Meaning Mapping (PMM) is a variation of concept mapping developed by John Falk, of the Institute for Learning Innovation, Maryland, USA (Falk, 2003) for use in informal learning environments. While concept mapping requires the technique to be taught to learners, PMM can be used with no prior experience on the part of the learner, and has uses both in and outside the classroom. The paper is based on an empirical study of school groups visiting an astronomical observatory in Gauteng, South Africa (Lelliott et al., 2005). The data collection involved structured interviews on astronomy concepts such as stars, the Sun and gravity (not reported here) and the students drawing Personal Meaning Maps with the phrase ‘space stars and planets’ used as the ‘prompt’ for investigating for their ideas on this topic. Theoretical Basis The technique of Personal Meaning Mapping is based on the concept maps developed by Novak and collaborators in the 1980s (Novak & Gowin, 1984). Concept maps have their roots in Ausubel’s theory of meaningful learning (Ausubel et al., 1978), whereby it was realized the finding out what individuals already know about a topic was a worthwhile endeavor. In concept mapping, a subject is taught how to map out their own understanding of concepts on a sheet of paper, and connect these concepts with appropriate connectors. In the technique of concept mapping, there is sometimes a ‘correct’ concept map, drawn by an expert, against which the subject’s map can be compared and scored. Much of the concept map analysis that has been developed over the past 20 years is based on this type of comparison (McClure et al., 1999) and it has proved a useful technique for both pedagogy and the study of conceptual development, especially at the school and tertiary education level. There have been a number of variants of concept mapping since the technique was first developed by Novak and a technique used by Morine-Dershimer (1993) and a recent one by Leinardt and Gregg (2002) are probably the closest to PMM. In a study of conceptual change, Morine-Dershimer asked student teachers to make a concept map depicting their view of the important components of teacher preparation by providing the phrase “teacher planning”. Two semesters later, the students repeated the task, and then compared their post-course map with their original map. Leinardt and Gregg used a similar method with pre-service teachers visiting a museum. They counted the number of ideas on each person’s pre-visit and post-visit map, and then analyzed the structure of the maps to detect whether the structure of the webs and any reorganization of information had changed. Like these variants of concept mapping, the method of PMM creates no expectations of what the learner should know, either before or after the visit. Other mapping techniques have been used in educational research, such as flow diagrams (Davidowitz & Rollnick, 2005) and vee diagrams (Trowbridge & Wandersee, 1998). Critiques of concept mapping have been made by Kagan (1990) and Ruiz-Primo and Shavelson (1996). Kagan noted in his critique of concept maps that they were used to assess short-term change rather than long-term gain. He also remarked that studies often compared subject maps with a target ‘master’ map. Many studies made claims that the map reflects an individual’s actual cognitive structure, and that the maps may reflect their ability to “reproduce the structure of the discipline” (Kagan, 1990) rather than show real changes in students’ cognitive structures. Ruiz-Primo and Shavelson (1996) sounded warnings about using concept maps for assessment purposes, and stressed the need for further research on the relationship between the maps and students’ cognitive schema. Apart from the fact that I used PMMs to demonstrate short-term rather than long-term gain, these criticisms do not apply to my study, as I used the maps principally as a basis for further questioning rather than at face value. I chose to use PMM as a technique to complement my other data collection method of structured interviews. The structured interviews focused on Big Ideas in astronomy (Lelliott, 2006), and could be regarded as a form of ‘pre- and post-test’ related to a traditional expectation of cognitive learning. In contrast, PMM is more suitable to the museum environment, and requires no preparation on the part of the participants (Adelman et al., 2000; Falk, 2003). How PMM is conducted PMM is a technique developed specifically for museum learning, in which an individual’s knowledge and views about a particular topic are investigated prior to the person entering the museum and again after the visit. Specifically, PMM is carried out in the following manner: 1. Prior to the visit to the museum, the person is given a sheet of paper, in which a word or phrase is written in the centre. He or she is then asked to write or draw anything that comes to mind in relation to the word or phrase. This can be factual information, ideas, beliefs, or any other related opinions, and is written in a specific color on the paper (e.g. blue). 2. The investigator then has a short interview with the individual, and, investigates the ideas he or she has already written on the paper, recording any elaboration of ideas in a different color ink from the original (e.g. red). 3. After the visit, the person is given their original paper, and asked to make and changes or additions to what they have already written on the paper. According to Falk (pers. comm.) and Luke (pers. comm.), it is crucial that the original paper is given back to the person, rather than asking them to fill a new one. It ensures that they do not feel that the investigator is ‘wasting their time’ by asking them to repeat what they have already done, and it allows them to alter their original ideas. This contrasts with methods normally used in concept mapping. The corrections and additions the individual makes to his or her map use another color ink (e.g. black). 4. Finally, the investigator carries out another interview, based on the alterations and additions carried out in step 3. The investigator writes these (again using the person’s own words) in a different color ink (e.g. green). Examples of PMMs are shown below in Figures 2 and 3. In my study, the environment for data collection was quite different to many studies using PMM. Like Luke (1998), my data was collected in the school classrooms of the selected participants in the study. I initially gained permission of the school Principal and relevant class teachers, and obtained informed consent from the students and their parents. I then addressed the students in class and explained that I am researching their forthcoming visit to one of the study sites. After handing out blue pens to each student, I explained that I wanted them to write whatever they think about when seeing the words in the centre of the sheet of paper. Before giving them the paper, I then showed an example on the chalkboard, using the word “Johannesburg”. I asked the class what things came into their heads when they saw that word on the middle of a piece of paper. Using examples from the class, I then wrote their suggestions on the chalkboard, linking the words they suggested to the central word “Johannesburg”, or to words they have already put forward, as shown in Figure 2. Figure 1. Example of initial PMM drawn on chalkboard Once I had answered questions, and considered that students had got the idea of the technique, I handed out the PMM sheet that I had prepared in advance for the study. The ‘prompt’ words in the middle of this sheet were “space, stars and planets”. Falk recommends that thorough piloting of the prompt is necessary (Falk 2003), and I did this in one of my pilot schools, using a combination of words including space, Earth and stars before deciding on the final wording, which elicited the most fruitful responses. I then asked the students to write what they could tell me about these words. I stressed the following, that: • Even if they were not sure about a particular issue, they should feel free to write about it. • This was not a test. • They could use words in their home language if they wanted. • They could do drawings. • They could write about their feeling and beliefs I then gave the students time to complete the PMM. This varied from about 5 minutes, to a maximum of about 30 minutes. Most students would complete the map within 15 to 20 minutes. In order to ensure anonymity, I wrote a number on the PMM as each student completed it, and compiled a class list with the students’ names and the PMM numbers. I could then cross reference each student against their own PMM, but anyone seeing a map would not be able to identify which student had completed it. As they completed their PMMs, students handed them to me. I then selected which students I wanted to interview, on the basis of what they had written or drawn in the PMM. Analysis One key difference between many analyses of concept mapping and PMM is that there is no ‘correct’ map developed at any stage, against which the PMM is scored. In fact Falk (2003) maintains that such a form of analysis would be counter to the philosophy of PMM in the context of museum learning. For Falk, there is no correct answer or series of answers that a museum visitor can be expected to come up with in relation to their visit. Unlike the school classroom, or the university lecture, where the students would be expected to learn particular scientific concepts or facts, the learning which takes place in museums is personal, context-bound and idiosyncratic. A PMM is therefore an individual’s personal construct of whatever learning took place as a result of their visit. Falk (2003) recommends a particular method of analyzing PMMs, which involves looking across four dimensions of learning: extent, breadth, depth, and mastery. Extent examines vocabulary while breadth categorizes concepts used by the learner, and a comparison can be made between his or her pre-and post-intervention learning. Depth measures a learner’s understanding of the concepts used while mastery assesses the overall quality of the understanding and how the learner makes use of it. While Falk suggests that PMMs can be analyzed both quantitatively and qualitatively, most of the studies in which they have been used have been dominated by quantitative techniques (Adelman et al., 2000; Falk et al., 1998). My study being qualitative in nature, implied that I forego extensive quantitative analysis, and make individual learners the units of analysis. In this respect the personal meaning maps and accompanying interviews were very helpful, as they provided details of the sort of learning not captured in my structured interviews. In addition, although not analyzed for all the dimensions suggested by Falk, I was able to use the PMMs to assist with some descriptive statistical data, such as the number of astronomical vocabulary words (‘extent’ in Falk’s terminology) used by each participant in the study. Nonkululeko’s learning Nonkululeko’s personal meaning map (Figure 2) drawn before her visit to the science centre was similar to those of many other students in my study. She listed the nine planets together with some brief facts about several of them. For example that Jupiter is the biggest planet and Mercury is the closest planet to the Sun. She referred to stars as being “a lighting thing” created by God, and that they are our “friends, family and negbour” (sic). She also referred to stars being at the galaxy and Milky Way. She stated that space consists of open space, containing planets, stars, galaxy and the Milky Way. When probed about her PMM, she confirmed that “God created stars so that it can shine at night”. Although she knew the term galaxy she was unable to explain its meaning or its relationship to the term Milky Way. She further referred to a spaceship and rocket, although she found difficulty in expressing herself here. She also appeared to have differing ideas on aliens. Having said she doesn’t believe in them in the structured interview, she mentioned that some planets have them in the PMM. Figure 2. Nonkululeko’s Pre-visit Personal Meaning Map After her visit to the science centre, Nonkululeko added considerably to her PMM (Figure 3), filling the reverse side of the paper with numerous facts. Several of these facts were a repetition of her pre-visit PMM, such as her reference to the nine planets, Pluto being the coldest, Mercury being the hottest and stars being in the galaxy. However, she wrote down several new pieces of information, including the following: • She “saw which bottle goes high and low”. This was reference to the ‘Coke bottle rockets’ which students used in an activity. • Additional planets to the nine named ones. • Additional facts about the nine planets. • Black spots on the Sun. • Various features of Mars: water, land, and orbit. • A description of the Moon landing and the time taken to get there • A star bigger than the Sun. Figure 3. Nonkululeko’s Post-visit Personal Meaning Map Further probing of several of the ideas was not carried out to any great extent, due to time constraints in her interview. Her understanding of a galaxy was still minimal: “A galaxy I think is where the stars stays and the moon and the solar system and the everything”, but she understood that it would contain thousands and thousands of stars. Her belief in aliens was still ambivalent: in the post-visit PMM she wrote that she believed in them, but when questioned she said she did not, although she had read about them in a magazine. I consider that Nonkululeko’s changes to her PMM are incremental additions to her knowledge of basic astronomy resulting from her visit to the science centre. All the additional facts she referred to in her PMM were examples of facts, activities or demonstrations she participated in during her visit. Implications for Personal Meaning Mapping in teaching and research The reason why I considered these additions to Nonkululeko’s PMM as important is that when questioned about aspects of space and stars during the structured interview data collection, Nonkululeko showed no improvement in her knowledge or understanding. The structured interview could be regarded as a more traditional pre- and post-test of astronomy knowledge, which demonstrated a range of ability across the 34 students in the study. Nonkululeko was at the bottom end of this range, suggesting that the visit had made no difference to her knowledge of astronomy. However, the use of PMM, in which there was no expectation of specific prior knowledge, showed that Nonkululeko had acquired several facts about astronomy which might not have been identified by traditional tests. This suggests that Personal Meaning Mapping might have uses in normal classroom settings, as well as the way is it currently used in out-of-school learning. Teachers could, for example, ask for their students to complete a PMM prior to starting a topic, in order to determine the prior knowledge of the class. A relatively brief analysis would enable a teacher to tailor his or her teaching to the class’ prior knowledge, as well as target individuals and groups for enrichment or remediation. As Personal Meaning Mapping is a relatively new technique, no analysis or evaluation of the technique has yet been published. During my study, I found no particular drawbacks in using PMMs as a data collection method, but I have the following recommendations for their use by future researchers: 1. Where possible, spend adequate time in preliminary analysis of the PMM prior to the initial interview. Similarly, spend adequate time in analysis of the PMM before the second round of data collection, and prior to the second interview. Unfortunately, in the sequence of data collection involved in museum visits, this is not always possible. 2. In a pilot study, experiment with the two alternatives of handing the original PMM back to the participants for addition/correction and asking them to complete a new PMM. Falk strongly recommends the former for museum visitors, for ethical reasons due to their time constraints and the inconvenience they are being put to. For school groups time is less of an issue and they are ‘used to’ formal and informal testing as part of their school work. A comparison between these two alternatives might therefore be of value. 3. It might be worth doing some additional ‘testing’ of the technique as part of the piloting. For example, if a PMM is given to a group of people, who then repeat the procedure some time later, with no intervention between the two processes, is there any difference between what people complete on the PMM? To what extent does the very act of completing a PMM result in possible changes in people’s thinking about the topic? References Adelman, L. M., Falk, J., & James, S. (2000). Impact of national aquarium in baltimore on visitors' conservation attitudes, behavior and knowledge. Curator, 43(1), 33-61. Ausubel, D., Novak, J., & Hanesian, H. (1978). Educational psychology: A cognitive view (2nd ed.). New York: Holt, Rinehart and Winston. Davidowitz, B., & Rollnick, M. (2005). Development and application of a rubric for analysis of novice students’ laboratory flow diagrams. International Journal of Science Education, 27(1), 43-59. Falk, J. H. (2003). Personal meaning mapping. In G. Caban, C. Scott, J. H. Falk & L. D. Dierking (Eds.), Museums and creativity: A study into the role of museums in design education. Sydney: Powerhouse Publishing. Falk, J. H., Moussouri, T., & Coulson, D. (1998). The effect of visitors' agendas on museum learning. Curator, 41(2), 107-120. Kagan, D. (1990). Ways of evaluation teacher cognition: Inferences concerning the goldilocks principle. Review of Educational Research, 60(3), 419-469. Leinhardt, G., & Gregg, M. (2002). Burning buses, burning crosses: Student teachers see civil rights. In G. Leinhardt, K. Crowley & K. Knutson (Eds.), Learning conversations in museums (pp. 139-166). Mahwah, New Jersey: Erlbaum. Lelliott, A. D. (2006). Learning about astronomy: A case study exploring how grade 7 and 8 students experience sites of informal learning in south africa. Unpublished PhD, University of the Witwatersrand, Johannesburg. Lelliott, A. D., Rollnick, M., & Pendlebury, S. (2005). Investigating learning about astronomy - a school visit to a science centre. Paper presented at the Proceedings of the13th Annual SAARMSTE Conference, Windhoek, Namibia. McClure, J. R., Sonak, B., & Suen, H. K. (1999). Concept map assessment of classroom learning: Reliability, validity, and logistical practicality. Journal of Research in Science Teaching, 36(4), 475-492. Morine-Dershimer, G. (1993). Tracing conceptual change in preservice teachers. Teaching and Teacher Education, 9(9), 15-26. Novak, J., & Gowin, D. (1984). Learning how to learn. New York: Cambridge University Press. Ruiz-Primo, M., & Shavelson, R. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33(6), 569-600. Trowbridge, J. E., & Wandersee, J. H. (1998). Theory-drive graphic organizers. In J. J. Mintzes, J. H. Wandersee & J. D. Novak (Eds.), Teaching science for understanding. A human constructivist view (pp. 109-131). San Diego: Academic Press.