Enzyme kinetics is a difficult subject for students to learn and for tutors to teach. During the practicals included in the biochemical courses at the Faculty of Chemistry of Universidad Nacional Autónoma de México, we found that the students acquire good training in the calculations to obtain kinetic parameters such as Km, Vmax, optimum pH, etc., but, when they are questioned about the significance of the values and their relationship to enzyme catalysis, many confusing ideas arise. To provide extended practice opportunities that could aid in the learning process we developed computer software that simulates an enzyme assay for lactate dehydrogenase, named enzsimil, that was used as well as the practical sessions. We tested three different levels of guidance to work with enzsimil, scripts where the students had to follow detailed (guided), intermediate (semiguided), or minimal (unguided) instructions, and for comparison, one group had a session of solving problems in class extracted from the program (class), and one more group had no additional sessions (control). After their respective sessions, the students either wrote a report or completed their script and undertook a laboratory practical. At the end, an exam was applied to all students. The reports and exams were graded, and the performance of the experimental groups was subjected to a statistical analysis. In addition, we carefully read the answers trying to identify the more common errors and misconceptions. The study revealed that there are statistically significant benefits in the use of the program. The semiguided scheme was more convenient to help the student in the short term for the preparation of better reports, while in the long term, both the semiguided and unguided groups performed equally well. These results are discussed in terms of the convenience of guided or unguided teaching strategies in computer-assisted learning.
Enzyme kinetics in the Biochemical course has proven to be too complex for the 3rd-year students of different chemistry areas. Their knowledge of basic algebra and how they interpret graphs requires improvement. This situation is a crucial obstacle to their understanding of several subjects and in particular to the specific processes of enzyme kinetics . When we searched for ways to solve this problem, we found that extending the laboratory practice was expensive and time-consuming.
As an alternative solution, we developed a computer software program (named enzsimil)11 that simulates an enzyme assay for lactate dehydrogenase. With this program the student carries out a large number of enzyme assays in a short space of time. In this way practice should reinforce the basic understanding of enzyme kinetics. Nevertheless, during the development of the program a number of questions arose:
Will the simulator be a teaching aid that improves the performance of the students in the learning and comprehension of enzyme kinetics?
What should be the role of the tutor during the use of the program?
Should the program be used without guidance to produce a cognitive conflict and the spontaneous process of equilibration as suggested by Piaget  or as a teaching medium specially aimed to help students in learning concepts and strategies as proposed by Vygotsky  or somewhere in the middle ?
With these questions in mind, an experimental model was designed with different teaching methodologies with which the students used enzsimil.
In the present article, we describe the results obtained with five distinct groups during five different terms. The article is divided in three parts. Under “Part I: Use and Application of the Experimental Model” the experimental model used and how it was applied is described. Under “Part II: Comparison of the Students' Performance with and without enzsimil Using Different Teaching Modalities” the students' performance with or without the use of the software under the teaching modalities employed is subjected to a statistical evaluation. Finally, under “Part III: Interpretation and Discussion of Results” an interpretation of our findings is advanced, and a discussion is presented about the relationships between enzsimil, the teaching methodologies used, and the students' performance.
PART I: USE AND APPLICATION OF THE EXPERIMENTAL MODEL
Description of the Simulator
Kinetic Model and Algorithm—
The program was written in Pascal and compiled under MS-DOS 6.0, so it can be run on most PC computers; it can also be run under Windows™ in an MS-DOS-emulated environment. In designing the program a bi-bi ordered fully reversible kinetic model was employed (Scheme 1, steps 1–5) , considering the formation of two dead end complexes (Scheme 1, steps 6 and 7) when the first substrate to enter and the first product to leave were simultaneously bound to the enzyme, in both directions . At the beginning of each calculation the program corrects the rate constants for the various reaction steps for temperature using the Arhenius equation  and determines the amount of active enzyme remaining after the preincubation period, if this was requested, assuming five ionic forms for the free enzyme (Scheme 2, E+2, E+1, E0, E−1, and E−2), which differ substantially in their thermal stability (Scheme 2, rates k11 to k15). Of these five forms, only three were able to bind the substrates (Scheme 2, E+1, E0, and E−2), and the substrate-bound enzyme forms had enhanced thermal stability (Scheme 2, rates kn2, kn3, and kn4 smaller than k11 to k15). The program introduces pH effects on catalysis by correcting the kinetic constants in the steady state rate equation for pH . For these calculations the three active ionic enzyme forms were considered to have different binding and catalytic properties. Then, at 1 × 10−4 s intervals, the distribution of enzyme forms is calculated from the steady state distribution equations deduced from the kinetic model by the King-Altman method, and the amount of each form surviving the total time elapsed is calculated from its respective first order rate law. The differential form of the steady state rate equation is used to calculate the amount of products formed during the 1 × 10−4 s elapsed, and the concentrations of each substrate and product are updated. These operations are repeated as many times as necessary to complete the desired assay time. Conditional sentences were introduced at some points in the algorithm to prevent numerical errors resulting from calculations with extreme values of the variables. For instance, high temperatures result in “overflow” errors during the attempt to calculate the exponentials in the Arhenius equation for denaturation rates, but since large denaturation rates imply that the activity goes to zero after a few milliseconds, product accumulation is negligible anyway, so the error can be avoided by setting the enzyme activity to zero.
The screen observed by the user is relatively simple, mostly self-explanatory, and is depicted in Fig. 1. After entering the conditions and pressing F9, five values of the absorbance of NADH at regular time intervals are given by the program. The absorbance is calculated from the Lambert-Beer equation using a molar extinction of 6.22 μM−1 cm−1. The experimental error is simulated by random changes of the substrate, product, and enzyme concentrations (within 5% of the given value), and in addition, a random noise within ±0.0005 absorbance units is added to the calculated value. Absorbance has an upper limit of 3.154 absorbance units. These last two calculations intend to simulate experimental and instrumental limitations found in a real laboratory. The final result as change of absorbance per minute is obtained by non-weighted linear regression of the sampled points.
Design of the Experimental Model
When enzsimil was initially used, the general comments of the tutors from the biochemistry department were that the students did not understand what they were doing and neither did they improve their performance in the examinations. To test how enzsimil could be a more efficient teaching and learning aid, four different teaching modalities were designed [8–10] to be used during and after the work with enzsimil. These modalities were Guided (n = 32), Semiguided (n = 26), Unguided (n = 20), and Class (n = 10); a Control group (n = 31) was also included. The students were ranked according to their general mark average in their career and sequentially sorted (with the aid of a computer spreadsheet) into the four teaching modality groups. In this way, each group had students with a similar distribution of general averages. The Control group consisted of all the students registered in one group of the biochemistry course for one term; with that exception, the other four modalities were applied in each term. A brief description of each modality follows.
In this modality, the students were given a printed document (script) containing full detailed instructions about:
How to carry out an enzyme assay using the computer program (section 1).
How to perform the experiments and the values of the parameters to be used in those experiments. These parameters are as follows: effect of pH (section 2), effect of temperature (section 3), effect of enzyme concentration (section 4), and effect of substrate concentration (section 5).
Closed questions were included that required the students to analyze their results and asked them to reach conclusions, giving a set of conditions where the LDH22 activity should be maximal (section 6). The questions required an understanding of how the variables act and an analysis of possible causes for the phenomena observed. At the same time, this modality did not give room for the student initiative to explore other assay conditions or to discuss aspects that were not included in it. This modality was worded so that most possible mistakes made by the students while studying enzyme kinetics using enzsimil were constrained.
This second script had minimal instructions about how to make an enzyme assay in the computer program (only section 1 of the Guided script) and a short text to remind the students that the enzyme activity must be “linear in the time interval selected and reasonably high.” To achieve this, they had to find the assay conditions through several changes in the variables that influence the enzyme assay. Further, they had to choose the range of values for the same parameters studied in the Guided script. These sometimes gave them unusual results, deviating from the classic behavior obtained with the Guided script or in an experimental session. The script also included some general questions to encourage students to analyze their results. To do that successfully, it was essential that they reviewed the subject in biochemistry textbooks as their results could have been atypical. Finally, they had to deduce optimal conditions for an LDH assay. The Semiguided modality allowed the students to make mistakes in the experiments they were performing and to discuss what they thought was relevant to the study.
In this third modality, the script included only section 1 and a list of the parameters to be investigated. The students have to work out for themselves whether the results they obtained were in accordance with what they had studied or whether the conditions they chose were suitable for the enzymatic assay. After a week, they have to write a typical laboratory report as is customary in the faculty of chemistry. The report included an Introduction (with a general hypothesis), Materials and Methods, Results, Discussion, and Conclusions (they did not have to follow any particular script). In the Unguided modality, we found frequent cases of non-classic enzyme kinetic behavior due to unsuitable choices for conditions, for instance the enzyme activity being too low to see any change due to unsuitable pH, temperature, etc. or a very narrow range of the values of the factor under study (e.g. pH = 7–8).
This fourth modality has exactly the same script as the Guided modality, but data were included as obtained from the computer program. The students solved the Class script in a classroom with a tutor present to assist the students when they had difficulties with the questions. However, they were not allowed access to the computer program.
There was a fifth option, the Control group, in which the students did not have access to the computer program nor did they carry out any enzyme kinetics exercises in the classroom.
Other Sessions and Evaluation
Following the computer session, the students had a week to fill in the script (except for the Control group) or to write the typical laboratory report. In the 2nd week, they had a practical session where they perform experiments regarding the same aspects they had studied with the computer program. In the 3rd week, the students had a discussion session with the tutor where their results (experimental and from the computer program) were analyzed and discussed with the whole classroom, and at the end of that session, they took an exam.
The students were presented with an exam of multiple choice questions concerning:
Previous knowledge acquired in subjects other than biochemistry or in the theoretical biochemistry lectures,
Specific knowledge that allegedly had been taught during the computer program and the practical session,
The application of the knowledge recently obtained, and
A last section consisting of the interpretation of graphs elaborated with data from experiments similar to those performed with the computer program.
In the last section (iv) they had to apply the abilities and knowledge supposedly acquired in the solution of two problems. The first one asked the student to tell the difference between two isozymes based on the kinetic response of those enzymes, and the second one asked the student to choose the conditions where an enzyme activity should be maximal. The data for both problems were presented in plots similar to those expected from the students in their previous work. The results were subjected to statistical analysis using the SigmaStat statistical package (Jendel Corp., San Rafael, CA).
PART II: COMPARISON OF THE STUDENTS' PERFORMANCE WITH AND WITHOUT ENZSIMIL USING DIFFERENT TEACHING MODALITIES
Does the Computer Program Influence the Performance of the Students in Scripts and Exams?
To answer this question we started looking at possible differences in the marks of the students in scripts of those groups that did not use the program compared with those who worked with the program in a fully Guided, Semiguided, or Unguided manner. The statistical analysis of the data (Table I) revealed no significant differences between the Guided and the Semiguided groups: both performed better than the Class group with the performance of the students in the Unguided group being the worst.
The above results indicate that the students who used the program with Guided or Semiguided scripts performed well. However, it is not so surprising that the use of the program was not essential for the average student to score a mark above 60% (minimal mark to pass). At the same time, it is noticeable that the worst group was the Unguided group. A reasonable conclusion of these results is that although the program seemed to be a good teaching aid, guidance is essential, especially if we expect the students to make an ordered analysis of those factors, which enable them to reach some conclusions. Additional observations on each group follow.
Guided and Semiguided Groups—
The Guided group was given specific instructions regarding the magnitude and ranges of the numerical variables to be tested, whereas the Semiguided script only suggested which parameters should be tested and how to decide whether the response obtained is acceptable. Therefore, the fact that the Guided and the Semiguided groups performed equally well indicates that the knowledge and experience gained in the investigation of the adequate conditions for the basic enzyme assay lacked relevance in relation to the ability of the students to give an adequate description of the effects of the various parameters to be studied when answering the scripts.
It is important to mention here that to mark the Unguided group report (as they did not have any script to answer) we followed the criterion of awarding points for each parameter affecting the enzyme that they tested successfully and additional points if the experience was ordered enough to allow them to describe the characteristics of the response even if the description was only superficial.
It is worth pointing out that the Class script was identical to the Guided protocol except that the results of the experiments were already in the text (obtained from the program). The data in Table I indicate that although the difference between the Class and Guided protocols was not very large (7%), it was statistically significant (p = 0.05). This result reveals that there is some benefit associated with the students' involvement in getting the numeric values. On the other hand, students in the Unguided group, who were only told what variables they should change and what was the main goal of the experience (to find the best set of conditions for an enzyme activity assay), had even worse performances than the students in the Class group.
Are There Particular Aspects of the Subject Where the Performance Differences Are More Evident?
Second, we analyzed each distinct section of the scripts and found that the student groups performed differently in these sections. The script started by asking the students for a set of initial conditions where the enzyme assays give an activity that is linear in the time interval employed and where the activity is reasonably high, in other words that gives them enough room for changes in enzyme activity. Afterward they were asked to analyze the effect of several variables that can be freely manipulated in the program, and finally they had to give a set of conditions where the enzyme activity should be maximal.
The complexity of these questions is low for the first task (Assay conditions, section 1), medium for the second group of tasks (pH, section 2; T, section 3; [E] section 4; and [S], section 5), and high for the Optimal conditions (section 6). The results in Fig. 2 show that the students performed well in finding an initial set of Assay conditions, but they had a slightly poorer performance in the second group of tasks, particularly in regard to the effects of enzyme and substrate concentration, probably because these last variables are less related to everyday life experience in the school of chemistry than temperature or pH. Finally they had bad marks in the Optimal conditions. In our point of view, the most interesting facts are (see Fig. 2) that the Class group performed better in the second group of tasks, but both the Unguided and Class groups had equally bad performances in the Optimal conditions. On the other hand, the Guided and Semiguided groups had better marks in the first and second group of tasks and higher marks in the Optimal conditions as compared with the Unguided and Class groups.
This behavior is statistically corroborated in Table II as the Unguided group has the lowest marks in all the script sections (Fig. 2); the only significant difference within the group performance in the different script sections is between the Temperature and the Optimal conditions, the sections with the group's largest and smallest percentage of correct answers. In the Class group the significant differences start with the enzyme concentration where the decrease in correct answers occurs to a greater extent than in previous sections (Table II and Fig. 2).
In the Guided group the percentage of correct answers continuously decreases, so there are significant differences between each script section, although their marks are higher than the marks from the Unguided and Class groups and similar to the marks from the Semiguided group (Table II and Fig. 2). The Semiguided group has the larger percentage of correct answers in all the script sections (Fig. 2); nevertheless, they had difficulties with the effect of substrate concentration and with the Optimal conditions, which proved to be difficult for all the groups, so in those sections the correct answers diminish in a significant way with respect to the previous sections (Table II).
The data strongly indicate that a teaching guide is essential for the students' understanding with regard to enzyme kinetics. Some conventional guidance, in addition to the use of the computer program, facilitates the comprehension of the different subjects in the scripts and hence the students' capability of reaching conclusions. A completely Unguided teaching strategy is not advisable at least if the evaluation closely follows the students' work in the subject. In addition we found of interest the following particular observations on the performance of each group.
The Guided group performed statistically significantly better than the Unguided group with respect to the Assay conditions (section 1, Table III) and the effect of pH and of the enzyme concentration (sections 2 and 4, Table III). Teacher guidance during the elaboration of experiences in the computer program seems to be, once more, important for the comprehension and learning of how an enzyme is assayed, how the pH affects the reaction rate and the enzyme stability, and how the enzyme concentration alters the reaction rate.
The Semiguided group was more successful than the Guided group in sections 2 and 4 (Table III). In fact, this is the group with the largest percentage of correct answers in the questions of the sections regarding pH effects and enzyme concentration (sections 2 and 4). In principle, the main difference between the Guided and the Semiguided group is that the students in the Semiguided group had more freedom to work with the computer program. Therefore, it is reasonable to assume that this was the one factor that contributes the most to a better performance of the Semiguided group with respect to the other groups; however, it is important to mention that the students in the Semiguided group may have spent more time than the Guided group in choosing the range of values for the variables under study, thus, along with the freedom of choice, they also were forced to collect a larger set of data regarding the enzyme responses to various factors.
The Unguided group is the one that had the largest number of differences with the Semiguided group apart from the enzyme assay conditions (section 1, Table III); as we have mentioned before, the pH is one of the parts with which the Unguided group seems to have problems as they had the worst results (section 2, Fig. 2). One of the probable causes for this is that students are reluctant to choose values of pH larger than 7; they think that as enzymes are in the human body it is only natural that the enzymes work better at pH values around 7. They simply do not discuss their results even when they are different from what they expect. The same happens with temperature (section 3). For them, the optimum temperature is around 30 °C, so they do not try temperatures higher than that, or if their results show that the optimum temperature is above 30 °C, they do not discuss why; in fact, the Unguided group seems to be the only one that had problems with the study of the effect of temperature. We have interpreted these findings as an indication that the lack of guidance makes them prone to be misguided by their own preconceptions.
The most difficult subjects for all the students were the effect of the enzyme and substrate concentrations upon the reaction rate (sections 4 and 5): the Unguided group was the worst one in these matters; they made the same mistakes that we found in the other groups but more frequently. The most common explanation for their results obtained in both subjects is that the curve obtained from the variation of the enzyme concentration is similar (most of the time) to the one of the effect of the substrate concentration; thus for them, the effect is the same: the enzyme is saturated in both curves by the substrate even if in the first case the substrate was held constant. Since at high enzyme concentrations the limitations in the assay quickly results in NADH exhaustion resulting in roughly the same rate for every enzyme assay, they believed that the enzyme was saturated and the maximum velocity was reached.
Regarding question 6 where the students have to conclude with the Optimal conditions for measuring LDH activity, the Class and the Unguided groups were the ones with major problems making correct conclusions; a larger fraction of the students in the Unguided group were unable to change their preconceptions of the best conditions for an enzyme, so they concluded that the optimum values for the temperature and pH are 30 °C and pH 7. Another common conclusion is that the optimum enzyme concentration is the one that corresponds to the start of the inflection of the curve or to the value obtained at the plateau. The plateau here is an unexpected result for most students since textbooks indicate that the response to enzyme concentration should be linear. Most students fail to interpret this plateau as a limitation of the assay and attribute the curve of the enzyme response to substrate concentration. Many of them also tend to interpret saturation as a bad condition for the enzyme; thus, they choose the inflection point of the curve as an optimum substrate concentration. The same mistaken ideas are found in the other groups but in a smaller fraction of the students.
Although the questions given to the Class group and the Guided group were identical, the performance of the Class group was significantly inferior to that of the Guided group in section 1 (Assay conditions section, Table III). As the Class group did not obtain the results from the computer program, this suggests that the use of the computer program in finding a set of suitable conditions for the enzyme assay may help in the understanding of how some variables affect the reaction rate (Table III).
The Class group also has a lower percentage of correct answers than the Semiguided group in sections 1 and 4 (Assay conditions and enzyme concentrations, Table III). However, the effect of enzyme concentrations also proved to be difficult for the students from all the groups. In comparison with the Unguided group, the performance of the Class group was significantly superior in sections 1 and 2 (Table III). Section 2 is about the effect of the pH upon the reaction rate. As pH is a factor that all the students review in subjects other than biochemistry, familiarity with this factor could be a reason for the best performance of the groups in this section. The enzyme concentration effect, however, is new to them.
Students' Performance in Exams
Week 1 involved those students who worked with the computer program (Guided, Semiguided, and Unguided groups) and the Class group that only did enzyme kinetics exercises. Week 2 involved a traditional practical in the laboratory of the four groups, and in the 3rd week they had the exam. The Control group just had a traditional practical in the laboratory (Weeks 1 and 2) and the exam in Week 3. The Control group had no contact with the program and was not given a script of any kind before the experimental session.
Table IV shows the comparison of the various groups' performance during the traditional written examination. The first observation is that all the groups have an average mark above 60. Surprisingly, the Unguided, the Semiguided, and the Class groups obtained the best marks with no significant differences between them. The marks of the Unguided group were significantly higher than those of the Guided and Control groups, and this was statistically significant. This suggests that given time the average student manages to pass the exam; those who were given the freedom to literally “play” with the program made the most of their later work. In addition, the poor performance of the Control group must be interpreted with care because, although given the same time to prepare for the exam, these students were not required to answer any script and may have dedicated considerably less time to the study of the subject. In any case, in our experience, teaching enzyme kinetics demands special requirements. One single practical session (4 h each) on enzyme responses to various factors seems hardly enough for the average student to get a basic understanding of this subject. Thus, working with the computer program or with exercises before the practical session should have beneficial effects, which may help to explain the results in Table IV.
To identify specific learning problems within the different teaching modalities studied, we decided to look for differences in the students' performance in each question of the exam. Those questions where the average marks of the students were at or below 65% were selected, and we searched for any evident particular trend in the wrong answers given by the different teaching modality groups. We translated from Spanish the questions and the answers.
Question 1: How do you measure the rate of a chemical reaction?
a. Quantifying the amount of synthesized substrate
b. Calculating the rate of absorbance/change over time
c. Measuring the changes in product concentration in a given set of time
d. Measuring the time that it takes for the substrate to be exhausted
e. Making a graph of ln[Product] versus time
Percentage of correct choice: 57.1 (c)
Percentage of most frequent incorrect choice: 39.4 (b)
In this question, the most frequent mistake was the conception that the experience performed in the program and in the practical session can be applied to all enzyme reactions. This mistake was, however, uncommon in the Class group. We believe that this is due to the participation of the tutor overseeing the group during the class session because the students could have made mistakes related to the calculation of enzyme activity while working on the exercises, and the tutor probably made the observation of how the exercises could be extrapolated to other situations.
Question 2: If the enzyme concentration is increased in an enzyme assay what happens?
a. The reaction rate does not change.
b. The product accumulation is faster.
c. The reaction rate diminishes abruptly.
d. All the above statements are incorrect.
Percentage of correct choice: 31.6 (b)
Percentage of most frequent incorrect choice: 54.0 (d)
This was a difficult question, and we believe that the difficulty lies in the way of stating the correct answer because it demands the combination of two apparently unrelated pieces of knowledge. First, it requires the definition of reaction rate, and second, it requires the response of the enzymatic reactions to increases in enzyme concentration. Here most students simply fail to identify a right answer, which may be in some way related to the problem found in the first question.
Question 8: If we add more reactant to a chemical reaction mixture, whose reaction order is different from zero, the most likely outcome will be:
a. The reactant consumption will be slower.
b. The reaction rate will become smaller because of substrate accumulation.
c. The reaction activation energy diminishes.
d. The reaction rate does not change.
e. At the beginning of the reaction the reactant consumption will be faster.
Percentage of correct choice: 64.7 (e)
Percentage of most frequent incorrect choice: 23 (d)
In this question, the students had to use a piece of knowledge that they could not acquire from other subjects' experimental sessions because in those subjects they did not analyze the general effect of reactant variations in chemical reactions. In the biochemistry experimental session they studied the specific effect of changes in substrate concentration in enzymatic reactions. It is not surprising that many students answered that the addition of more reactant results in no change in the reaction rate just as when the enzyme is saturated with substrate and the addition of more substrate makes little difference. However, it is noteworthy that the general response of the Unguided group was different; many thought that the reaction was slowed down by the addition of more reactant. One of the interpretations of this misconception is that the students of the Unguided group rely upon the common human experience of the reduced efficiency of individuals who are given an excessive amount of work, that is to say they are replacing a scientific framework with a common human experience. However, other explanations are feasible, and clarification of this point may well deserve further studies.
To elucidate whether the students that answered one question correctly were the same students that correctly answered other questions, we made an analysis by Pearson Product Moment Correlation. In the Control group questions 1 and 8 showed significant positive correlation (p = 0.003); nevertheless, questions 1 and 8 had an average of 58 and 38% of correct answers, respectively. It looks as if the students that had a correct idea of how the rate of a chemical reaction is measured were more likely to know how the concentration of the reactant affects the reaction rate. It is worth pointing out that the Control group had the lowest mean for question 2. The failure to give the right answer for question 2 could be the result of the students' inability to identify the enzyme as the cause of the decrease in the absorbance as we observed in some laboratory reports or exams of those students who did not have contact with the program or with class exercises. In fact, when the students were asked to explain why this decrease is produced, they answered that it is caused by the pH or the temperature, both of which are physical phenomena common in their past experiences.
Another correlation exists between questions 2 and 8 in the Unguided group (p = 0.03) as the means of questions 2 and 8 are in the range of other groups; this could signify that the students who understand how the reaction rate is altered by the enzyme concentration also had a correct idea about how the increase in the concentration of the reactant affects this rate. As the students of the Unguided group are forced to interpret the effects of various variables over the reaction rate by themselves, it is possible that they paid more attention to this particular aspect than the other groups because under guidance they may not have been so aware of their misconceptions.
As stated in the exam description, in the last section of the exam the interpretation of two graphs from the students is required. The first one obtained a low percentage of correct answers as described below.
Question 17: the students were presented the graph in Fig. 3 together with the text included in the legend to Fig. 3.
Percentage of satisfactory answers: 41.5
Percentage of unsatisfactory answers: 58.5
In this question the students were asked for knowledge of various characteristics of Km: its definition, meaning, and understanding of how Km affects the shape of a substrate saturation curve of an enzymatic reaction. Here most students were only able to describe the shape of the curves but could not identify that the different shapes were related to the enzyme affinity for the substrate. We believe that as simple as the Km concept seems, most students learn the mechanical procedures to derive Km values from raw data, as deduced from the answers to other questions, but they hardly understand the meaning of the number that they have calculated and its relation to the enzyme behavior. In other words, most students focused on calculation procedures and descriptive knowledge but put little emphasis on analysis, abstraction, and judgement.
PART III: INTERPRETATION AND DISCUSSION OF RESULTS
Clearly, giving the students the opportunity to use the program brought benefits because the Control and Class groups showed poorer performance in both the scripts and the exam. The fact that the Class group showed a similar behavior to the Unguided group strongly argues in favor of having a session of work with the computer simulation because in the short term their results are equivalent to a traditional lecture, and in the long term, using the program benefits the learning process as shown by the Unguided group, which had a better performance than the Class group.
For those groups that had contact with the program, the analysis of the scripts seems to support different conclusions than those supported by the analysis of the exam performances. The fully or partially guided schemes led to better performance in the script reports, but the full or partial lack of guidance resulted in better exam marks. However, when considered in more depth, the Unguided group was indeed guided a posteriori because their reports were marked and corrections to their mistakes were annotated, and with these, their reports were given back to them before they do the laboratory practical and study for the exam. So a definite, closed answer to the value of guidance cannot be drawn from our data. Nevertheless, our data do say that some level of guidance is required if the intention is to favor an ordered study of enzyme behavior through enzsimil, especially if the students are required to organize and interpret the data shortly afterward.
On the other hand, lack of guidance seems to make students prone to be misguided by their own preconceptions . For instance, in the script where they have to find the optimum conditions for the LDH activity assay, the Class and the Unguided groups were the ones with major problems making correct conclusions. Many concluded that the optimal values for the temperature and pH are 30 °C and pH 7. Also mistakes such as considering the optimum enzyme concentration in an assay as the one that corresponds to the start of the inflection of the curve and the interpretation of enzyme saturation as a condition applicable to all curves showing a plateau or regarding saturation as a bad condition for the enzyme are more frequent in the Unguided group than in other groups.
We believe that if the goal is to encourage the student to make the most of later work then it is better to give the students some freedom of choice during the computer simulation session, provided that the tutor reviews and comments on their work later. In that sense, a Semiguided strategy partially covers both situations and may be recommended if the tuition goals are not sharply defined. In addition, a more subtle adjustment of the level of guidance is always possible and even advisable.
Perhaps the most significant conclusion of this study is that the best teaching strategy depends on what is to be achieved. To that respect, training “report-makers” or “exam-answering technicians” is hardly ever the main goal of education; and thus a study on how the use of computer simulations and similar tools affects meaningful, long term learning is required. Unfortunately such study requires tracking the development of the students in their professional life and is beyond our current capabilities. In addition, differences in teaching goals may help to explain why some studies found that traditional teaching is as effective as more active approaches like problem-based learning , while other studies found benefits in the latter approach .
In addition to the aspects mentioned in the previous paragraph, we think that the tutor must be aware that his role should be in accordance with the different teaching modalities. In the full guidance modality, scripts and exams from the students will all be similar, while the partial guidance, or the lack of it, will require the tutor to make use of wider criteria and a deeper knowledge of the subject in marking the students' work because the students will use their own individual strategies to solve problems. Therefore, their results will be heterogeneous but not necessary wrong.
Finally, there is extremely valuable information in the students' scripts, reports, and exams regarding concepts of enzyme kinetics that are particularly difficult to teach. We are currently working on their analysis, which will be the subject of a future article.
Table Table I. Statistical comparison of the performance in scripts of the groups of students in a self-teaching session of written exercises (Class) or in a self-teaching session with the computer program
a The number in parentheses indicates the rank difference from the Dunn's test comparison.
b Statistically significant with p ≤ 0.05.
Those working with the program were given a brief outline of factors to investigate (Unguided), a list of experiences to perform with minimal details (Semiguided), or a detailed guide to the required experiences (Guided). The mean represents the percentage of correct answers. The statistical test applied was the Kruskal-Wallis analysis of variance in ranks and multiple comparisons by the Dunn's test of differences in ranks.
Table Table II. Significance of rank differences between each script section mark within different teaching modalities
The letters of the teaching modalities where the respective comparison gave a statistically significant difference (p ≤ 0.05) are shown. G, Guided; S, Semiguided; U, Unguided; C, Class.
C, G, S
C, G, S
C, G, S
C, G, S, U
Table Table III. Comparisons between the median values of the correct answers from each section of the scripts
The table shows only the number of the sections where statistically significant differences between groups, two at a time, were found according to the Dunn's test (p = 0.001). Section numbers are as follows: 1, Assay conditions; 2, pH effects; 3, Temperature effects; 4, Enzyme concentration dependence; 5, Substrate concentration dependence; 6, a conclusion with a set of conditions for Optimal activity.
1, 2, 4
1, 2, 3 4, 5, 6
Table Table IV. Statistical comparison of the mean percentage of correct answers to the exam questions by the experimental groups (Guided, Semiguided, Unguided, Class, and Control)
a From the Tukey test.
b The difference was significant at 0.05 level of p.
The Control group did not use the computer program nor did they use enzyme kinetics exercises in class. Since the normality assumption was fulfilled by these data (Kolmogorov-Smirnov with p = 0.05), the statistical test applied was the one-way analysis of variance followed by the Tukey test for all pairwise multiple comparison.