Based on evidence of difficulties, potential sources of classified difficulties were isolated. A new three-phase single interview technique (3P-SIT) was designed to explicitly investigate the nature of the above three factors.
LIST OF TABLES
LIST OF ABBREVIATIONS!
1 INTRODUCTION AND AIMS
So in lieu of the above reasoning, the author considers it crucial to conduct a thorough investigation of students' difficulties with the interpretation of ERs, especially, but not exclusively, in the field of biochemistry. As shown in the diagram, Chapter 4 reports on the use of the research framework of Grayson et al. 2001) · identifying and classifying problems in the interpretation of three selected ERs of IgG structure and function.
2 LITERATURE REVIEW
Introduction
Without attempting to survey all the work ever published, an overview is given of the research thought to have the most application to learning and teaching with external representations in science.
The nature of external representations in science
The desire to use the term ER as a label to include all graphic displays used in science education was born. Given the terminological diversity and the aim of this review, it is likely that all image forms used in science education are covered under one banner.
Visual literacy and science education
Regardless of how we define it, visual literacy encompasses the idea of visual thinking, which Seels (1994) considers the ability to visualize through images. Lowe (1987) and Fry (1981) emphasized that visual literacy should also include the ability to construct ERs (eg, drawing diagrams).
Cognitive mechanisms responsible for ER interpretation
In the literature, mental models are discussed with a great deal of reference to the interpretation of scientific ERs. The role of mental models in the interpretation of scientific ERs will remain an important pedagogical component of this thesis.
The nature of reasoning with ERs in science
Well-structured ERs help learners build meaningful mental models that can be efficiently managed in working memory (e.g., Glenberg and Langston, 1992; Mayer, 1989b). Third, graphic constraint concerns how ER markings limit the range of interpretations that can be generated from the ER (eg, Chenget aI., 2001; Stenning and Oberlander, 1995).
Use of different types ofERs for learning and teaching in science
- Learning and teaching with staticERs that portray structural phenomena
- Learning and teaching with static ERs that portray spatial phenomena
- Learning and teaching with static ERs that portray dynamic phenomena that are physical in nature
- Learning .and teaching with static ERs that portray dynamic phenomena that are abstract in nature
- Learning and teaching with static ERs that are graphic-word in nature
- Learning and teaching with animated ERs
- Learning and teaching with multimedia ERs
In the 1960s-1980s, Francis Dwyer studied students' interpretation of ERs representing the structure of the human heart. In one example, Dwyer (1967) examined students' interpretation of ERs of the heart across a visual realism continuum.
Summary
There is little empirical evidence to show that animated ERs are better than static ERs for learning. As with static ERs, novices rely more on labels that stand out than on the importance of labels when interpreting animated ERs.
3 METHODS
Introduction
Student and course context
Second-year students who complete the full one-year biochemistry course may choose to study the subject as part of the third and final year of their science degree. The student and subject context of the study influenced the structure of the theoretical framework used in the thesis.
Theoretical framework
- Biochemistry context
- Science Education context
In the following section, we examine the science education context of the theoretical framework used in this study. The above sentiments form the basis for the science education context of the theoretical framework used in this thesis.
Methodological framework
- General methodological approach
- Data collection instruments
- Nature of the methods used to collect data on students' interpretation of ERs
- Written instruments
- Clinical interviews
- Student-generated ERs
- Data Analysis
- Validity and Reliability of the data collection instruments
- Nature of validity and reliability in the current project
- Using the four-level framework to pursue validity and reliability of the data
- Validity and reliability of the written instruments
As part of the qualitative design, the methods used in the current study were naturalistic and concerned people as instruments (e.g., Lincoln and Guba, 1985, p. 39). Obtaining student diagrams was an important feature of the methods used in this study to obtain student interpretations of ERs. During the inductive analysis of the data in the current project, patterns of meaning and evidence were allowed to emerge from the data themselves (e.g. Anderson and Aresenault, 1998;.
In this regard, the researcher in the current project was concerned with providing a natural and detailed description of the patterns that emerged from the data (Gallet et al., 1996).
Summary
Commenting on issues of validity and reliability in science education research, Sanders (1998) urged emergency room researchers to "open their minds" (p. In response to this sentiment, one general way to expand the validity and reliability of research instruments and later.Thus, this study relied heavily on the concept of triangulation (e.g.
The discussion has also offered relevant views regarding the validity and reliability of the methods used in the current project.
4 STUDENT DIFFICULTIES WITH ERs OF IMMUNOGLOBULING (IgG}AND ITS
INTERACTION WITH ANTIGEN
Introduction·
Methods
- Study groups and ERs under study
- Screening the ERs for potential student difficulties
- Probing students' interpretation of the ERs
- Analysis and classification of student responses
The bivalency of the IgG molecule is represented in Fig 4.1A by two antigen molecules (shown in dark red) attached to the variable regions of the antigen-binding domains of the antibody. One of the light chains is shown in light red, the other in light blue. One of the heavy chains is shown in dark red, the other in dark blue.
Students' understanding of ERs (Fig 4.1) was investigated at the end of the module by means of written tests and interview questions.
Results and discussion
- Process-type difficulties
- Structural-type difficulties
- DNA-related· difficulties
It is evident from the above quotations that some students gave scientifically acceptable interpretations of the three ERs in relation to process type difficulties (Table 4.2). 34; The colored region (gray) represents different amino acid residues associated with the backbone (black line) of the ant body." [response to probe 6; ERA. To show that the two different IgG sites are not of the same kind." [answer to inquiry 1;.
ER D may have contributed a source for the latter, the nature of graphic markings.
Summary and Conclusions
This could be a topic for future research where the actual source of the difficulties could be further clarified. Given the above occurrences in relation to each ER, analysis of the data suggested that the nature of the ER and its graphical markings played a major role in students' ability to interpret them. In addition to the nature of the ER and its graphic markings being a major source of students' difficulties, the data showed that students' reasoning processes also had a major effect on their ability to interpret the ERs.
In addition to the nature of ER and students' thinking process being the main source of students' difficulties, data analysis revealed that the nature of students' conceptual knowledge also affects their ability to successfully interpret ER.
5 A THREE-PHASE SINGLE INTERVIEW TECHNIQUE (3P- SIT) FOR GENERATING EMPIRICAL DATA ON
THE FACTORS AFFECTING STUDENTS'·
INTERPRETATION OF ERs
Introduction
Basic design,structure and rationale of the clinical interview instrument
After running the instrument, there is a progression through each of the stages from, Stage 1 to Stage 2 and then to Stage 3 (Fig. 5.1). Thus Phase 3 allows the researcher to generate information about the role, effect and nature of ER in isolation. In doing so, we provide examples of personalized surveys for each of the interview phases and the rationale behind their design.
We also present selected student responses and show how the data can be analyzed to uncover information corresponding to each of the factors.
Participants and ERs used to test the instrument
For the convenience of the reader, a flip-out page of all three ERs (Fig. 5.2) used in this study is provided on p. Two interviews, each with different participants, were conducted for each of the three ERs (Fig. 5.2), giving a total of six interviews. Two of the three ERs (Fig. 5.2 E and F), which were used to pilot the interview instrument, were obtained from the immunology textbook (Roitt, 1997) prescribed for the course, while a colleague (Jackson, press . comm.) the remaining ER (Fig. 5.2 G).
An electron micrograph (Fig. 5.2 E) can be considered a "real" representation of the interaction of antibody and antigen, a space-filling model (Fig.
Probe design and analysis of students' responses
- Phase 1: Generating and analysing data corresponding to students' conceptual knowledge (C)
- Phase 2: Generating and analysing data corresponding to students' reasoning processes (R)
- Phase 3: Generating and analysing data corresponding to the mode of representation (M)
The success of the interpretation of the ER was measured by comparing the student's conceptual knowledge after exposure to the ER (Phase 2) with the conceptual (propositiona1) knowledge represented by the ER. The student suggests that the realistic graphic nature of the depicted· antibodies and antigens makes the·· ER challenging to interpret. The student also provides further information about which ER features may also have had a positive effect on the interpretation of the ER.
Analysis of the response obtained from the student above suggests that the graphical (textual) functions corresponding to the “-log” function on ER G may have contributed to failed reasoning with ER.
Implications of 3P-SIT as a data-gathering instrument
By generating and analyzing data from the Phase3 probes, the researcher can identify how the external nature of the ER itself influences ER interpretation. Therefore, the data generated during Phase 3 corresponds to the last of the factors influencing students' interpretation of ERs as observed in Chapter 4, namely the way in which the desired scientific phenomenon is represented in the ER(M ). Third, the analysis of the data from Phase 2 shows how the researcher can obtain information about students' reasoning processes (R), firstly with the interpretation of the graphic markers in the First Aid and secondly with the involvement of students in reasoning about their conceptual knowledge. .
Fourth, the analysis of the data from phase 3 shows how the researcher can obtain information about the role and effect of the representation mode (M) on students' reasoning processes.
6 A MODEL OF FACTORS DETERMINING STUDENTS" , , '
ABILITY TO INTERPRET EXTERNAL REPRESENTATIONS
Introduction
Methods
- Participants and descriptions of the external representations
- Empiricaltesting ofthe model (stage 5)
- Analysis of the interview data
Fourth, conducting various thought experiments as well as extensive discussion of the expression model with the supervisor helped to establish the validity of the model and whether it should be modified. Of crucial importance during the fifth phase was to validate whether the resulting consensus model fulfilled its purpose and to consider what the actual applications and limitations of the model would be. Empirical testing of the model was carried out, using 3P-SIT (Chapter 5), in order to investigate the nature of the interaction between the factors of the model, to clearly form.
Details regarding the analysis of the data obtained with the 3P-SIT instrument are discussed in Section 5.4 (Chapter 5).
Results and Discussion
- Development of the model
- Validation of the Reasoning Factor (R)
- Validation of the Representation Mode Factor (M)
- Validation of the Conceptual-Mode (C-M}Factor
- Validation of the Conceptual-Reasoning-Mode Factor (C-R-M)
Represents the nature of the CONCEPTUAL (PROPOSITIONAL) KNOWLEDGE REPRESENTED BY IS and its symbolism. We defined the C-M factor as representing the nature of the conceptual (propositional) knowledge represented by ER and its symbolism. It includes the scope, complexity and solidity of the knowledge that ER represents (Table 6.1).
In terms of the above student's interpretation of the propositional knowledge (C-M) represented by ER F, in order to successfully visualize the ER (R-M) showing only one Fab arm of the antibody (M), the student must include his/her conceptual knowledge (R-C and C), represented by ER, and also reasoning with ER (R-M).
