Multiple choice questions (MCQs) are used as a preferred assessment tool, especially when testing large classes like most first-year Economics classes. However, while convenient and reliable, the validity of MCQs with a negative marking rule has been questioned repeatedly, especially with respect to the impact of differential risk preferences of students affecting their probability of taking a guess.
In this article we conduct an experiment aimed at replicating a situation where a student enters an examination or test once they already have an average from previous assessments, where both this and previous assessments will count towards the final grade. Our aim is to investigate the effect of a student’s aggregate score to date on their degree of risk aversion in terms of the degree to which they guess in this particular assessment.
A total of 102 first-year Economics students at the University of the Witwatersrand volunteered to participate in this study. The test used in this study did not count as part of the students’ overall course assessment. However, students were financially compensated based on their performance in the test.
Following an experimental design, students were allocated randomly into four groups to ensure that these differed only with respect to the starting points but not in any other observed or unobserved characteristic that could affect the guessing behaviour of the students. The first group consisted of students who were told that they were starting the multiple choice test with 53 points, the second group were told they were starting with 47 points, and the third and fourth groups were told that they were starting with 35 and 65 points respectively.
We show that entering an assessment with a very low previous score encourages risk seeking behaviour. Entering with a borderline passing score encourages risk aversion in this assessment. For those who place little value on every marginal point, entering with a very high score encourages risk seeking behaviour, while entering with a very high score when a lot of value is placed on each marginal point encourages risk aversion in this assessment.
The validity of MCQs combined with a negative marking rule as an assessment tool is likely to be reduced and its usage might actually create a systematic bias against risk averse students.
Average score; risk aversion; risk seeking; guessing; multiple choice questions.
A multiple choice test with a negative marking rule is a typical situation in which an individual who does not have complete knowledge of the correct solution is faced with a gamble of either omitting a question and receiving no reward, or answering a question and being penalised for an incorrect response. Hence, the performance or the associated payoff from such a test is dependent upon whether the student chooses to answer a question when confronted with such a gamble.
The use and grading of multiple choice questions (MCQs) is a well-established and reliable method of assessing knowledge in standardised tests and examinations within the education space. These multiple choice tests are advantageous to both the instructor and the student. From an instructor’s perspective, these tests offer increased accuracy and reliability in scoring (Walstad & Becker
However, multiple choice testing is not without its critiques. Incorrect answer options expose students to misinformation, which can influence subsequent thinking about content (Butler & Roediger III 2008). In addition, students expecting to write a multiple choice test also spend less time preparing for the test (as opposed to essay-based tests) as the answer is selected, and not generated (Roediger III & Marsh
Formula scoring rules, also known as negative marking, are frequently adopted as a means to discourage guessing by subtracting points for incorrect responses; unanswered questions are neither penalised nor rewarded (Holt
More importantly, risk preferences are likely to be non-randomly distributed which could introduce systemic bias. Ben-Shakar and Sinai (
The purpose of assessments is to measure the students’ knowledge through their responses to test questions. If the score obtained through MCQs not only reflects the student’s content knowledge but is also a function of other factors that affect the student’s probability of taking a guess, then the validity of MCQs as an assessment tool is reduced.
In this article we conduct an experiment to show how performance in previous assessments influences a student’s degree of risk aversion in a subsequent assessment. Our experiment aims to replicate a situation where a final grade for a course is calculated by finding the average of more than one assessment. In particular, this experiment looks at how a student might behave in a particular assessment once they already have an average from previous assessments, where both this and previous assessments will count towards the final grade. This is important for the literature on risk taking in general. More often than not, gambles do not occur in isolation but rather in the context of multiple gambles, where a final outcome will be a cumulative result of all such gambles. For example, a financial investment will probably be seen and assessed in the context of any other investments that an agent has undertaken.
The experimental nature of this study offers an advantage over a study based on observational data that was not derived from a controlled experiment. Differences in a student’s guessing behaviour as captured by observational data from an actual examination might be reflective of factors other than the student’s aggregate mark when entering the examination, while the controlled environment of the experiment aims to isolate the effect of the student’s aggregate mark.
Thus, the contribution of this article is twofold: firstly, the experiment has been set up in such a way as to allow us to isolate guessing behaviour by taking partial knowledge out of the equation. This is an advancement in the field of educational science in the sense that it has proven difficult to distinguish guessing behaviour from the effect of partial knowledge. Secondly, guessing behaviour in any particular assessment has, up to now, been looked at in isolation. This study looks at the effect of framing (Kahneman & Tversky
Our findings show that entering an assessment with a very low previous score encourages risk seeking behaviour. Entering with a borderline passing score encourages risk aversion in this assessment. For those who place little value on every marginal point, entering with a very high score encourages risk seeking behaviour in the particular assessment, while entering with a very high score when a lot of value is placed on each marginal point leads to risk averse behaviour.
This article will proceed as follows: the next section provides a description of the experiment conducted in this study. An analysis of the data and a discussion of the corresponding results is presented next and the last section concludes.
First-year Economics students from the University of the Witwatersrand were invited to participate voluntarily in the experiment. Participating students were randomly allocated to four different treatment groups as they entered the venue for the experiment. However, an attempt was made to stratify allocation by gender by giving male and female participants different colour tickets with their respective group allocations to ensure that there was a sufficient number of male and female students within each group, thus permitting the analysis of possible treatment heterogeneities along gender lines.
The decision-making experiment was conducted in a classroom setting. A multiple choice test (see
The expected points from guessing are computed using the equation
Participants were allocated to one of four experimental groups and were treated equally, aside from the points that they received before commencing with a multiple choice test. The first group consisted of students who were told that they were starting the multiple choice test with 53 points, the second group were told they were starting with 47 points, and the third and fourth groups were told that they were starting with 35 and 65 points respectively. The possible results of the multiple choice assessment ranged from 25 points to 85 points, encompassing the points that could be lost or gained in addition to the points that the students entered the experiment with. Since this was not a real test counting towards the final grade for the course, in order to incentivise students to try and maximise their total scores (so that the situation would replicate a real test situation) a financial payout to each student was provided on a rand (R1) per point basis. In addition, participants were told that a bonus of R50 would be given to each student who reached a score of 50 points or above after completion of the test. The possible results of the multiple choice assessment, ranging from 25 points to 85 points, corresponded to a range with regard to the monetary payoff, from a low of R25 to a high of R135 (taking into account the R50 bonus). The bonus of R50 for students reaching or surpassing a score of 50 points created a reference for each group. Two groups started off being close to the reference point (starting points 47 and 53) while the other two groups started off further away from the reference point (starting points 35 and 65). This allows us to investigate if the framing (relative distance to the reference point) affects the guessing behaviour of the students.
The experimental nature of this study also enables a causal interpretation between the initial number of points received by each student and the tendency to guess. Firstly, this relationship can be attributed to the exclusion of content knowledge as a covariate as participants could not reduce the number of possible solution options through their partial knowledge or obtain the correct answer to the question, since none of the alternative solutions provided was correct. Secondly, the random allocation of participating students into the four groups tried to ensure that no other observable and unobservable characteristics could explain differences in the guessing behaviour of students. Clearly, our interpretation of the results as a causal link depends on the assumption that the randomisation was successful in balancing our four groups in all other characteristics that might affect the guessing behaviour. While we try to test the balance of the four groups on a set of selected observed characteristics that are likely to be correlated with the students’ guessing behaviour, we cannot say with absolute certainty that the participants in the four groups only differ with respect to the allocation into the four groups. As such, it is possible that our results could still suffer from omitted variable bias.
We then looked separately at participants willing to accept a wage of R500 a month, and those not willing to accept this wage. Since the payoff in this study was in monetary terms, it was expected that students in greater financial need would attach greater value to every point. We proxied a student’s financial need status by the answer they gave to the question regarding whether or not they were willing to work for a wage of R500 a month. Those willing to work for R500 a month (considered an extremely low wage) were assumed to be in greater financial need than those who were not. As such, the aim was to analyse how guessing behaviour changed, depending on the value students put on each mark. Obviously students in more financial need would value each rand, and therefore each point in the test, more than a student who is financially better off. In a real test situation, students will differ in how they value each marginal point. While some students will be satisfied knowing they have a passing score (and not value each marginal point above that score), others will value each point they get over and above a passing score. Similarly, some students who fail will not care by how many points they fail, whereas others, even though they know they might fail, will still value each point and attempt to maximise their score (perhaps because they would then be eligible for a supplementary – second chance – exam).
In accordance with the university’s ethics policy, participation in this study was completely voluntary and participation or non-participation did not affect the students’ academic performance in any credit-bearing course. Furthermore, the identity of participants remained completely anonymous as the findings are reported in aggregate format. In addition, participating students were made aware of the full range of possible financial payoffs before they made their decision on participation.
This article was written with ethical clearance (protocol number: CECON/1031).
The study sample consisted of 102 participating students. Group 1 consisted of 28 students, group 2 of 25 students, group 3 of 24 students and group 4 of 25 participating students.
As part of the experimental design, students were allocated randomly to the four groups. This is to ensure that the four groups differ only with respect to the starting points but not in any other observed or unobserved characteristic that could affect the guessing behaviour of the students. As a test (reported in
Characteristics of composition of each group.
Variable | Group 1 |
Group 2 |
Group 3 |
Group 4 |
Observations | ||||
---|---|---|---|---|---|---|---|---|---|
Standard deviation | Standard deviation | Standard deviation | Standard deviation | ||||||
Male | 54% | 0.51 | 56% | 0.51 | 54% | 0.51 | 52% | 0.51 | 102 |
Willing to work for R500 per month | 54% | 0.51 | 48% | 0.51 | 54% | 0.51 | 44% | 0.51 | 102 |
Mathematics score (Matric) | 79.19 | 10.90 | 75.33 | 11.06 | 77.09 | 12.62 | 78.10 | 12.22 | 91 |
English score (Matric) | 76.00 | 6.51 | 74.27 | 7.57 | 72.39 |
6.43 | 74.86 | 8.23 | 92 |
Number of guesses (Mean) | 5.4 | 2.8 | 6.3 | 2.1 | 7.4 |
2.2 | 6.8 |
2.5 | 102 |
, significance at 10% level;
, significance at 5% level;
, significance at 1% level.
As can be seen in
Frequency of guesses taken by allocated group. (a) Group 1: Starting point 53; (b) Group 2: Starting point 47; (c) Group 3: Starting point 35; (d) Group 4: Starting point 65.
As is shown in
Guessing behaviour by group allocation.
Group | Average number of guesses | Median number of guesses | % of students responding to 0 questions | % of students responding to 9 questions |
---|---|---|---|---|
Group 1: 53 points | 5.4 | 6 | 7.1 | 17.9 |
Group 2: 47 points | 6.3 | 7 | 0 | 16 |
Group 3: 35 points | 7.4 | 9 | 0 | 54.2 |
Group 4: 65 points | 6.8 | 8 | 0 | 32 |
Effects by willingness to accept a monthly wage of R500.
Group | Willing to accept a monthly wage of R500 |
Not willing to accept a monthly wage of R500 |
||
---|---|---|---|---|
Average number of guesses | Median number of guesses | Average number of guesses | Median number of guesses | |
Group 1: 53 points | 5.5 | 6 | 5.3 | 5 |
Group 2: 47 points | 5.5 | 5 | 7 | 7 |
Group 3: 35 points | 7.5 | 9 | 7.3 | 9 |
Group 4: 65 points | 5.5 | 5 | 7.9 | 8 |
Gender effects.
Group | Number of guesses: Males |
Number of guesses: Females |
||
---|---|---|---|---|
Average | Median | Average | Median | |
Group 1: 53 points | 5.1 | 6 | 5.8 | 6 |
Group 2: 47 points | 6.3 | 7 | 6.3 | 6 |
Group 3: 35 points | 7.9 | 9 | 6.8 | 8 |
Group 4: 65 points | 7.4 | 8 | 6.3 | 7.5 |
With a successful randomisation, the analysis is simply a comparison of the differences in means. The analysis is therefore conducted using an ordinary least squares (OLS) approach, with the average number of guesses for the nine unsolvable items in the multiple choice assessment as the dependent variable (Y) regressed against the allocation into the four different groups (G) which enter the experiment with differential points. We use group 1 which received 53 points as the reference group.
However, should the randomisation not have led to a balancing of other covariates, we need to test if the inclusion of additional covariates (D) mitigates the effect of being in any one of the four assignment groups. We initially test this by adding only gender and the willingness to work for R500 per month. Additionally, we obtained English and Mathematics matric scores but only for a reduced sample (for 90 students in total). As a robustness check, we reduce our sample to students for whom we have a full set of characteristics and test if the inclusion of the full set of covariates affects the group coefficients. Thus, we estimate:
In
We conduct a second set of regressions which allows for the analysis of possible heterogeneities along the lines of gender and income status, in terms of how initial points affects guessing behaviour. This is done by using interaction terms such that:
In
Regression results.
Variables | 1 |
2 |
3 |
4 |
5 |
|||||
---|---|---|---|---|---|---|---|---|---|---|
Average number of guesses | Robust standard errors | Average number of guesses | Robust standard errors | Average number of guesses | Robust standard errors | Average number of guesses | Robust standard errors | Average number of guesses | Robust standard errors | |
Group 2 | 0.887 | 0.675 | 0.879 | 0.676 | 0.834 | 0.670 | 0.720 | 0.725 | 0.558 | 0.722 |
Group 3 | 2.024 |
0.682 | 2.022 |
0.684 | 2.027 |
0.677 | 1.850 |
0.715 | 1.711 |
0.719 |
Group 4 | 1.447 |
0.675 | 1.453 |
0.676 | 1.371 |
0.671 | 1.386 |
0.725 | 1.333 |
0.721 |
Male | 0.350 | 0.488 | 0.266 | 0.486 | - | - | 0.503 | 0.575 | ||
Accept R500 monthly wage | - | - | - | - | −0.839 |
0.486 | - | - | −0.852 | 0.518 |
English Matric mark (%) | - | - | - | - | - | - | - | - | −0.0276 | 0.0438 |
Mathematics Matric mark (%) | - | - | - | - | - | - | - | - | −0.0175 | 0.0258 |
Constant | 5.393 |
0.463 | 5.206 |
0.533 | 5.700 |
0.600 | 5.423 |
0.484 | 9.079 |
3.103 |
Observations | 102 | - | 102 | - | 102 | - | 90 | - | 90 | - |
0.090 | - | 0.095 | - | 0.122 | - | 0.081 | - | 0.145 | - | |
3.23 | - | 2.54 | - | 2.67 | - | 2.53 | - | 1.99 | - | |
Prob > |
0.0257 | - | 0.0447 | - | 0.0265 | - | 0.0621 | - | 0.0879 | - |
, significance at 10% level;
, significance at 5% level;
, significance at 1% level.
The additional robustness test reported in columns 4 and 5 confirms the consistency of these findings. The average number of guesses taken by students in group 3 and group 4 remain above the number of guesses taken by students in group 1. While the randomisation seems to have been successful with respect to balancing the included observed characteristics, we can see that for the reduced sample the inclusion of the matric marks in English and Mathematics marginally reduces the point estimate for group 3. However, the overall pattern remains consistent.
The
Regression results with interaction effects.
Variables | Average number of guesses (Willing to accept R500) |
Average number of guesses (Not willing to accept R500) |
Average number of guesses (Males) |
Average number of guesses (Females) |
||||
---|---|---|---|---|---|---|---|---|
Robust standard errors | Robust standard errors | Robust standard errors | Robust standard errors | |||||
Group 2: 47 points | 0.750 | 1.772 | 0.800 | 0.980 | 1.897 | 1.382 | 1.733 |
0.947 |
Group 3: 35 points | 3.639 |
1.503 | 2.000 |
1.104 | 1.088 | 1.299 | 2.933639 |
1.071 |
Group 4: 65 points | 1.250 | 1.664 | 2.000 |
1.047 | 2.031639 |
0.862 | 2.933639 |
1.014 |
Gender | 2.607 |
1.405 | −1.500 | 1.551 | - | - | - | - |
Group 2 * Gender | −1.857 | 2.046 | 2.367 | 1.999 | - | - | - | - |
Group 3 * Gender | −3.746 | 1.991 | 0.357 | 2.008 | - | - | - | - |
Group 4 * Gender | −2.964 | 2.111 | 1.300 | 1.719 | - | - | - | - |
Group 2 * R500 | - | - | - | - | −1.917 | 1.505 | −1.800 | 1.212 |
Group 3 * R500 | - | - | - | - | −0.107 | 1.642 | −0.111 | 0.931 |
Group 4 * R500 | - | - | - | - | −2.657 |
1.316 | −2.500 |
1.115 |
Constant | 4.250 |
1.344 | 6.000 |
0.880 | 5.769 |
0.719 | 5.067 |
0.847 |
Observation ( |
51 | - | 51 | - | 47 | - | 55 | - |
, significance at 10% level;
, significance at 5% level;
, significance at 1% level.
In this article we conduct an experiment aimed at replicating a situation where students enter an assessment with an existing average mark based on previous assessments. Our aim is to analyse the effect of the average grade to date on students’ guessing behaviour in a multiple choice test with a negative marking rule. This is important for the literature on risk taking in general, in that a gamble should not be seen in isolation, but rather in the context of multiple gambles, where a final outcome will be a cumulative result of all such gambles.
The experimental nature of this study offers an advantage over a study based on observational data that was not derived from a controlled experiment. Differences in a student’s guessing behaviour as captured by observational data from an actual examination might be reflective of factors other than the student’s aggregate mark when entering the examination, while in the experimental setting we can isolate the effect of the aggregate mark.
The incentive in this experiment is provided by way of a financial payout where money is paid for each marginal point, with a lump sum bonus being paid if the student’s final score is 50 points or above. This aims to replicate a situation where the vast majority of students would aim to pass a course (where 50 points here replicates a passing mark), with some students placing greater value on each marginal mark above or below that level than others. Since the incentive provided here is monetary, we look at two groups of students, where one group is in greater financial need than the other. We assume students in greater financial need will place a higher value on each point, corresponding to each rand. We show that entering an assessment with a very low previous score (in this experiment 35 points) encourages risk seeking behaviour. Entering with a borderline passing score (53 points) encourages risk aversion in this assessment. Additionally, for those who place little value on every marginal point (here students in less financial need), entering with a very high score (65 points here) also encourages risk seeking behaviour in the particular assessment. In fact, the effect of valuing every marginal point is most prevalent for students entering with the highest amount of points (65), where students in this group who value every extra point are more risk averse, that is, guess less than students in this group who don’t place as much value on each extra point.
The results can broadly be interpreted in the context of prospect theory as put forward by Kahneman and Tversky (
These results are important in light of literature advocating that risk averse students are biased against in multiple choice settings, since in real test situations most students would have partial knowledge, so that the expected value of guessing would actually be positive. So far the literature has identified females and, in particular, better performing females as being biased against in this regard. Here we identify a student’s existing average, apart from whether or not they are a good student (even though these are likely to be related), as a factor affecting risk aversion. Indeed students entering with a borderline pass are most risk averse from this perspective, and thus most biased against. Students with a borderline fail are second most risk averse. Students entering with very low scores seem to be the most advantaged by such a multiple choice test with negative marking (especially if they have some content knowledge) in that they have little to lose from guessing. Thus, previous results showing that worse students guess more could have a lot to do with the fact that they are entering with low scores. Whether or not students entering with very high scores are risk averse depends on the degree to which they value each marginal point. Students in this group who value each point are extremely risk averse, while those not valuing each point as much are extremely risk seeking. Thus, top students might be biased against for two reasons: (1) as identified by previous studies they have better content knowledge, making the expected value of a guess positive; and (2) they are likely to be entering with a very high score and, if they place a high value on each point, as shown in this study, they will be more risk averse for this reason too.
MCQ testing is a popular assessment strategy for large university classes like first-year Economics. However, in the light of our findings, the validity of multiple choice questions combined with a negative marking rule as an assessment tool is likely to be reduced and its usage might actually create a systematic bias against risk averse students. Budescu and Bar-Hillel (
Funding was provided by African Microeconomic Research Unit (AMERU) for this study.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
J.K. was involved in data collection and the preliminary analysis. A.R. and V.S. were involved in the design, analysis and contextualisation.
Student number: ____________________
Gender: ____________________
As a student, would you be willing to accept a job that pays a monthly wage of R500?
Yes ________ No ________
A group of modern economists who believe that markets clear very rapidly and that expanding the money supply will always increase prices rather than employment are the:
Monetarists Post-Keynesians Keynesians
What is the next term in the following sequence?
1, 1, 2, 3, 19, 34, 83, … … … … … … …
162 115 247
The Independent Labour and Employment Equity Action Plan was drafted by Mbazima Sithole in which year?
1996 1994 1999
Who is the author of the book titled: ‘Random Walks and Business Cycles for Dummies’?
Norman Gladwell Milton Savage John Friedman
The Law of Diminishing Demand states that:
As more of a particular good is demanded by the economy, less of that good is demanded by an individual. If good A is preferred to good B, then a higher demand for good B implies a lower demand for good A. As more of a good is supplied in an economy, the less of that good is demanded by the economy.
The Depression of 1978 occurred as a result of:
Severe drought affecting subsistence agriculture and herding. A banking panic which came about as a result of depositors simultaneously losing confidence in the solvency of the banks and demanding that their deposits be paid to them in cash. A decline in the population growth rate.
A Pareto Supremum refers to the allocation of resources in which:
All resources are directed to a single individual and no one can be made better off. It is possible to make all individuals better off. A socially desirable distribution is acquired through all individuals having a higher income.
The principle of Malthusian Dominance states that:
Gains in income per person through technological advances dominates subsequent population growth. An increase in the market price caused by an increase in demand dominates the higher price caused by a deficiency in supply. Increased demand for subsistence consumption eliminates the non-productive elements of the economy.
The Population Poverty Index estimates:
The percentage of the population living in poor regions. The number of people earning below $1 a day. The average worldwide population living below the poverty line.
A Walrasian Balanced Growth Path refers to:
The act in which excess market supply counteracts excess market demand. A situation in which output per worker, capital per worker and consumption per worker are growing at a constant rate. An efficient allocation of goods and services in an economy, driven by seemingly separate decisions of individuals.
Welcome to this decision-making experiment. My name is (author name). Before proceeding to the test questionnaire, please take note of the experimental instructions below. At the beginning of the test, you already have 53 points to start off with and you are now being placed in a test situation in which you may gain or lose points in addition to the 53 points. These additional points may be gained or lost through a multiple choice test with the following rules:
You are required to answer a multiple choice test consisting of 10 questions in total.
You will receive 2 points for each correct response; lose 1 point for each incorrect response; and no points will be gained or lost for each question that you choose to omit.
Your final amount of points will be calculated as 53 plus the number of points you obtain in the test.
The payoff you receive will be on a rand (R1) per point basis, i.e. you will receive R1 for each of your final amount of points. In addition, you will receive a bonus of R50 if your final score is above 50 points on completion of the test.
For example: If you receive 8 points for the test, your final amount of points will be 61 (53+8). In this instance, you will receive R61 + R50 bonus since your final score is above 50 points. Therefore, your final payout will be R111.
If however you receive –6 points (lose 6 points), for example, your final amount of points will be 47 (53–6). In this instance, you will receive a payout of R47 (you will NOT receive a bonus of R50 because your final score is below 50 points).
Note that your total payoff can vary between R43 and R123.
You have 20 min to complete the test.
Please note that your participation in this experiment is completely voluntary, involves no risk and will not affect your academic results in any way. Your answers to these questions are completely confidential and your identity will remain anonymous in the analysis of this study. If you have any questions regarding the instructions above, please feel free to ask. Should you wish to withdraw from this experiment, you may do so at any stage. Thank you for your consideration to participate in this experiment. Should you wish to enquire about my study or access my final results, please feel free to contact me at (author email address). You may now proceed to the test questionnaire.
Kind regards
<author name>
Welcome to this decision-making experiment. My name is (author name). Before proceeding to the test questionnaire, please take note of the experimental instructions below. At the beginning of the test, you already have 47 points to start off with and you are now being placed in a test situation in which you may gain or lose points in addition to the 47 points. These additional points may be gained or lost through a multiple choice test with the following rules:
You are required to answer a multiple choice test consisting of 10 questions in total.
You will receive 2 points for each correct response; lose 1 point for each incorrect response; and no points will be gained or lost for each question that you choose to omit.
Your final amount of points will be calculated as 47 plus the number of points you obtain in the test.
The payoff you receive will be on a rand (R1) per point basis, i.e. you will receive R1 for each of your final amount of points. In addition, you will receive a bonus of R50 if your final score is above 50 points on completion of the test.
For example: If you receive 8 points for the test, your final amount of points will be 55 (47+8). In this instance, you will receive R55 + R50 bonus since your final score is above 50 points. Therefore, your final payout will be R105.
If however you receive –6 points (lose 6 points), for example, your final amount of points will be 41 (47–6). In this instance, you will receive a payout of R41 (you will NOT receive a bonus of R50 because your final score is below 50 points).
Note that your total payoff can vary between R37 and R117.
You have 20 min to complete the test.
Please note that your participation in this experiment is completely voluntary, involves no risk and will not affect your academic results in any way. Your answers to these questions are completely confidential and your identity will remain anonymous in the analysis of this study. If you have any questions regarding the instructions above, please feel free to ask. Should you wish to withdraw from this experiment, you may do so at any stage. Thank you for your consideration to participate in this experiment. Should you wish to enquire about my study or access my final results, please feel free to contact me at (author email address). You may now proceed to the test questionnaire.
Kind regards
<author name>
Welcome to this decision-making experiment. My name is (author name). Before proceeding to the test questionnaire, please take note of the experimental instructions below. At the beginning of the test, you already have 35 points to start off with and you are now being placed in a test situation in which you may gain or lose points in addition to the 35 points. These additional points may be gained or lost through a multiple choice test with the following rules:
You are required to answer a multiple choice test consisting of 10 questions in total.
You will receive 2 points for each correct response; lose 1 point for each incorrect response; and no points will be gained or lost for each question that you choose to omit.
Your final amount of points will be calculated as 35 plus the number of points you obtain in the test.
The payoff you receive will be on a rand (R1) per point basis, i.e. you will receive R1 for each of your final amount of points. In addition, you will receive a bonus of R50 if your final score is above 50 points on completion of the test.
For example: If you receive 18 points for the test, your final amount of points will be 53 (35+18). In this instance, you will receive R53 + R50 bonus since your final score is above 50 points. Therefore, your final payout will be R103.
If however you receive –5 points (lose 5 points), for example, your final amount of points will be 30 (35–5). In this instance, you will receive a payout of R30 (you will NOT receive a bonus of R50 because your final score is below 50 points).
Note that your total payoff can vary between R25 and R105.
You have 20 min to complete the test.
Please note that your participation in this experiment is completely voluntary, involves no risk and will not affect your academic results in any way. Your answers to these questions are completely confidential and your identity will remain anonymous in the analysis of this study. If you have any questions regarding the instructions above, please feel free to ask. Should you wish to withdraw from this experiment, you may do so at any stage. Thank you for your consideration to participate in this experiment. Should you wish to enquire about my study or access my final results, please feel free to contact me at (author email address). You may now proceed to the test questionnaire.
Kind regards
<author name>
Welcome to this decision-making experiment. My name is (author name). Before proceeding to the test questionnaire, please take note of the experimental instructions below. At the beginning of the test, you already have 65 points to start off with and you are now being placed in a test situation in which you may gain or lose points in addition to the 65 points. These additional points may be gained or lost through a multiple choice test with the following rules:
You are required to answer a multiple choice test consisting of 10 questions in total.
You will receive 2 points for each correct response; lose 1 point for each incorrect response; and no points will be gained or lost for each question that you choose to omit.
Your final amount of points will be calculated as 65 plus the number of points you obtain in the test.
The payoff you receive will be on a rand (R1) per point basis, i.e. you will receive R1 for each of your final amount of points. In addition, you will receive R50 for participating in this test.
For example: If you receive 10 points for the test, your final amount of points will be 75 (65+10). Therefore, your final payout will be R125 (R75 + R50).
If however you receive –10 points (lose 10 points), for example, your final amount of points will be 55 (65–10). In this instance, you will receive a payout of R105 (R55 + R50).
Note that your total payoff can vary between R105 and R145.
You have 20 min to complete the test.
Please note that your participation in this experiment is completely voluntary, involves no risk and will not affect your academic results in any way. Your answers to these questions are completely confidential and your identity will remain anonymous in the analysis of this study. If you have any questions regarding the instructions above, please feel free to ask. Should you wish to withdraw from this experiment, you may do so at any stage. Thank you for your consideration to participate in this experiment. Should you wish to enquire about my study or access my final results, please feel free to contact me at (author email address). You may now proceed to the test questionnaire.
Kind regards
<author name>