Final Exams Preparation
Being a 4th year student in the biomedical science program, I’ve been through a lot of finals. Some good, some bad. I’ve learned a lot from those experiences and wanted to share a brief guide on some strategies and tips for doing well on final exams. I’m going to be breaking down my advice into the 4 following sections: pre-studying planning, scheduling, techniques for studying, and stress management. One thing I want to stress is some of the advice I give may not work for everyone, so you don’t have to stress about following it perfectly. If you think a piece of advice will help you, give it a go, and see how it feels.
It can be hard to find the motivation to go through an entire month solely focused on studying. The first thing to start with is to ask yourself why you want to do well on these final exams? Is it to pull a comeback from last semester? Is it to reach certain career goals in the future? Is it for pure satisfaction? Your reason can be just one or a combination of different reasons, and there is no right answer. What matters is finding that push to propel you forward.
Setting goals and calculating grades
It’s important to set goals for your courses in terms of your desired final grade. It gives you a threshold to aim for. Once you know the mark threshold you need to reach to achieve a certain grade, you can plan your study schedule as needed (I’m going to talk about study schedules shortly!). Before final exams, you should have a general idea of how well your classes are going based on the marks you’ve received thus far. Using those marks and the course breakdown in the syllabus, calculate what you have in the class right now along with what mark you need on the final exam to reach your desired goal. For components of the course that you don’t have a mark back for yet such as labs, you can estimate based on what you have so far and add it into the calculation while keeping in mind that it’s somewhat variable. Repeat the calculations for each course.
Having a solid study schedule is by far one of the most crucial parts of final exam prep. When I was in my first year, I went to the Faculty of Science Mentoring Center for some advice on preparing for finals and the mentors there helped me create a final exam study schedule. That study schedule was extremely useful for me and I continue to make them every time exams roll around. It may seem like a waste of time now, but it helps immensely in the long run. The reason is that with a schedule you already have everything you need to do is planned out. Once you have that, all you have to do is follow what you wrote down to do each day and adjust your schedule at the end of the day to match your progress. It also helps to keep track of progress visually and see how far you’ve gotten since the start and how much you have left to do. I definitely recommend finding some time to sit down and properly make a schedule of your own.
Making your own schedule
As a short guide to making a study schedule, I’d suggest compiling a list of all the lectures, and potentially chapters in the book, that are going to be covered on the final. Once you’ve done that and determined how much you need to study for each course to reach your goals, based on your mark calculations, you can start filling in a calendar for when you’re going to be studying which lectures for which courses. Keep in mind that your schedule may need some change and revision and that’s totally normal! It’s supposed to be this way so that your schedule is flexible. However, initially plan to finish your studying a little earlier than expected so that you have some buffer time in case you do need to shift your schedule a bit. In addition to your long-term schedule, I recommend keeping a daily checklist of tasks and crossing them out as you go along. It really helps to keep your goals in front of you and to see your progress.
If you are interested in making your own study schedule for final exams, Kyra, another mentor at the Science Mentoring Center, has created a guide to making a study schedule, stay tuned for that! Additionally, you can always also come down to the Mentoring Center and sit down with student mentors who can help you create a schedule of your own.
Exam Preparation Vectors
Dealing with specific types of exam questions
1. Multiple choice questions
Many students believe that to answer a multiple choice question they need only be able to recognise material and so need only do minimal revision. A well-written multiple choice examination, however, will require you not only to have a thorough knowledge of the subject, but also to be able to integrate information and to discriminate between similar answers.
- Carefully note the connecting words as well as the key words, in both the question stem and possible answers.
- Beware of double negatives. For example, the question might ask, ‘which of the following is true?’, and the first answer may read, ‘(a) it is not the case that. ‘
- Think carefully about sentences with words such as never and always.
- If there is an answer that you think is correct, check to make sure that the others are incorrect. You may find that you’ve been a bit hasty.
- Does the question contain any clues to the answer? Do the alternative answers give clues? Through careful analysis and a process of elimination it is possible to arrive at the correct answer even if at first sight you did not have any idea.
- If you are not quite sure of an answer, guess. Unless of course there is a penalty for incorrect answers. Determine before you begin whether or not there will be such a penalty.
- Do not pay attention to old myths such as, ‘if you don’t know the answer always tick the first box’ or, ‘always pick the shortest or the longest answer’. An educated guess after careful consideration of all the options is more likely to score an extra point.
- Another popular myth is that if you change your answer you are more likely to change it to an incorrect answer. In fact, studies have been done which prove just the opposite.
2. Short answer and essay questions
- Short answer: summarize the main points in the first sentence. This means that you will have to carefully plan your answer first. Also, if you run out of time your examiner will be able to see where you were heading with your answer.
- Essay: your introduction should outline the main points of your argument. The body of the essay should consist of a logical sequence of these ideas. Have one idea per paragraph and express the main point of the paragraph in the first sentence. The conclusion should provide a summary of your argument.
- Don’t rush into a question. Give yourself time to think about and plan your answer. Before writing, make jotting notes or a brief outline: this will aid your memory if you have a mental block later.
- If you run out of time or misjudge things and still have a question to go, then write notes/points. Set out a plan of how you would have answered the question if you’d had time.
- In a short answer question, content must be strictly relevant. Make sure that your answer is clear and concise, padding only wastes time.
- If appropriate, include clearly-labeled graphs or diagrams: these may help you to remember things which you have forgotten or provide you with a basis for your writing.
3. Problem-solving questions
Hierarchical Linear Modeling of Invested Effort in Dependence of Motivational Difficulties and Motivational Regulation
To differentiate between-person variations independent of time and within-person variations over time, the unconditional means model (Model 1) was estimated (Table 2). The variance components observed indicate substantial between-person variation (ICC = 0.18). 1 Though, more important in the context of this study is the quite large within-person variation, which was much larger than inter-individual differences. Thus, effort invested in the learning process is strongly characterized by variations with the learning situation rather than being a stable person-specific variable.
To explain time-specific invested effort and its interplay with motivational difficulties in dependence of motivational regulation, Model 2 was estimated (see Table 2). Aside from an average increase in invested effort over time toward the exam date, the results indicated general positive effects of motivational regulation on invested effort in the first instance as indicated by significant coefficients β01 and β02 (Hypothesis 1). The larger the extent of using motivational regulation strategies and the better the quality of this strategy use (as reported by the students in the pretest), the larger was the level of invested effort within the phase of preparing for the exam. Descriptively, the effect of quality of motivational regulation seems to be somewhat stronger than the effect of regulation quantity.
Concerning motivation difficulties that may frequently appear in learning processes, it was assumed that motivational regulation moderates (i.e., reduces) their negative impact on effort invested in the learning process (Hypothesis 2). The analyses show that motivational difficulties had, on average, a significant and relatively strong negative effect on invested effort (β10)—indicating that students invest lower levels of effort when they are faced with motivational problems during studying.
Relevant for testing Hypothesis 2 is the cross-level interaction effect between motivational difficulties and motivational regulation (β11 and β12). Here, quality of motivational regulation moderated the negative effect of motivational difficulties on invested effort. In other words, students with a high quality of motivational regulation showed higher levels of invested effort even if they are confronted with motivational difficulties. On the other hand, students with poor regulation quality were especially vulnerable for experiencing motivational difficulties during learning. The moderating effect of quality of strategy use on the connection between motivational difficulties and invested effort is depicted in Figure 1. A similar protecting effect was not found for the quantity aspect of motivational regulation.
To control for potential dependencies of the found relationships on previous achievement, the hierarchical linear analyses were repeated including the high school diploma grade as predictor for both, the intercept and the slope of motivational difficulties. All found effects were robust, i.e., did not change substantially in their size and stayed statistically significant.
Motivational Regulation and Achievement
Positive bivariate correlations between both aspects of motivational regulation assessed in the pretest and exam grade assessed in the follow-up were observed (see Table 1). Accordingly, students with a higher quantity of motivational regulation and a better quality of strategy use reported significantly better grades on the final exam.
Additionally, multiple regression analysis was conducted to simultaneously estimate the effects of both, quantity and quality of motivational regulation on achievement. The results are reported in Table 3. As expected, quantity as well as quality of motivational regulation proved to be moderately positive predictors of achievement in the final exam.
The regression analysis was repeated with previous achievement as a control measure—in order to rule out concerns that the effects of motivational regulation on achievement simply reflect that students with better prior performances are also better able to regulate their motivation while studying. Again, the effects were robust—previous achievement predicted achievement in the pertaining exam, but did not diminish the contributions of quantity and quality of motivational regulation on exam performance. Thus, quantity and quality of motivational regulation predicted achievement above and beyond the effects of previous achievement—which is in line with the assumption that motivational regulation has a causal effect on achievement.
The present study was designed to examine the role of quantity and quality of motivational regulation when it comes to motivational difficulties in the process of exam preparation. The use of a standardized learning diary approach provided unique insight into the everyday process of studying. This approach allowed us to capture impending motivational difficulties in the process, and to reconstruct the daily ups and downs of a study period. In contrast to a solely global assessment of self-regulated learning, the students did not have to generalize and abstract their motivational problems and invested effort from many situations to a global level. Another strength of the present work is the incorporation of both the quantity and quality of motivational regulation.
The findings indicate that motivational difficulties as triggers for motivational regulation are indeed situation-specific and can fluctuate strongly from day to day, rather than being a constant person-specific variable. The large proportions of within-person variance indicated that university students frequently struggle with keeping invested effort high while encountering motivational difficulties when preparing for an exam. The results confirmed that motivational difficulties lead, on average, to lower rates of invested effort in the learning process, which endangers study success.
In the present study, quantity and quality of motivational regulation were associated with achievement, but only a high quality of motivational regulation was able to moderate the negative effects of motivational difficulties on invested effort in the specific situations of the learning process. From a theoretical point of view this result pattern is sensible—only students who monitor and adapt the application of motivation regulation strategies should be able to overcome motivational difficulties.
It is important to note that all found effects were robust also after controlling for previous achievement. Consequently, concerns can be ruled out that the found relationships may be due to common correlations with prior achievement or simply reflect causal effects from achievement on motivational regulation. Instead, they indicate that quantity and quality of motivational regulation have an incremental effect on effort and achievement above and beyond the effects of previous achievement.
Despite these limitations, it can be concluded that motivational regulation is a relevant and demanding aspect of self-regulated learning. The findings point out that motivational difficulties can endanger learning success on a daily basis, as they result in lower rates of invested effort. The results of this study indicate that quality of motivational regulation is an important buffer and protective factor in this process. The findings are in line with the theoretical assumption, that both a high quantity and a high quality of motivational regulation enable students to cope with motivational difficulties, to show high levels of invested effort despite such difficulties and, eventually, to improve their academic performance. The findings, alongside other studies in the field (e.g., Leutner et al., 2001), indicate that not only the quantitative aspect, but also regulation quality is an important aspect of motivational regulation that should be in focus when assessing and training motivational regulation. While choosing a strategy often depends on personal preferences and the individual learning history, all students can profit from improvements to the metacognitive control of their strategy implementation.