UMAT One

Section 1 of the UMAT® Exam is the logical reasoning and problem solving section. The questions in this section assess your ability to comprehend, draw logical conclusions, reach solutions by identifying relevant facts, evaluate information, pinpoint additional or missing information, and generate and test plausible hypotheses. Unlike in GAMSAT® Exam, the material can be based on a large variety of stimuli and there are no real trends in the types of topics utilised. As no prior knowledge is expected and the approaches to solving questions are not influenced by topics, attempting to classify questions by topic would not be useful. Instead, 4 broad categories of questions can be distinguished based either on the way the information is presented or on the type of reasoning required to solve the question. The categories are “Data interpretation”, “logical reasoning”, “scientific experiment” and “problem solving”. UMAT® Exam preparation courses can really help you become better at answering these types of questions, as they provide you with a large number of test questions with worked answers. Although many core skills and strategies are common to solving all categories of questions, specific challenges and solving approaches, which I have attempted to describe below can be more frequently associated with each question type. 
 

Data Interpretation

In this type of question, information is presented in a schematic form such as a graph, a chart, a table or a diagram. The schematic information must be deconstructed and translated in order to extract relevant information and identify correct statements.The main challenge in this type of question usually resides in understanding the way the information is presented, extracting the relevant information and sometimes in performing simple quantitative manipulations of the data. Depending on the complexity and amount of information represented, more than one sub-­question can follow a figure. If the schematic is especially complex, the first sub­-question may be designed with a view to guide students in deconstructing and understanding the information. It is therefore advised that answering MCQ sequentially is preferable for compound questions.
 

Logical reasoning

This type of question requires to make simple deductions based on the information provided in a short extract. The extract can be given context related to science e.g. describe a biological process or a natural phenomenon, a sociological trend or it can be a simple syllogism problem. Challenges in this type of question include understanding and synthesizing information, identifying relevant facts and using deductive reasoning to reach logical conclusions. While information has to be deconstructed from schematic form in data interpretation, it is often useful to synthesize and convert information into schematic form in these questions. More than one sub-­question can be based on an extract, with longer or more technical extracts usually followed by 2 or 3 MCQ. As for the previous type of questions, the first questions may be designed to help you synthesise the information from the extract or provide clues for following sub-questions. 
 

Scientific experiment

An extract describes a scientific experiment (or a study) and presents the main findings. You must use logical reasoning to understand experimental design and aims, interpret data and generate plausible hypotheses. Depending on how results are presented, challenges in this type of question can be similar to that of data interpretation (deconstructing schematic data) or logical reasoning (synthesising information from an extract). In addition, there is a strong emphasis on identifying patterns in data. This type of question requires you to use not only deductive (find the answer to a specific problem, based on a general rule you know to be true), but also inductive (extrapolate a general trend or principle based on specific data) and sometimes abductive (generate plausible hypotheses based on incomplete data or findings) reasoning. The ability to distinguish between correlation and causation is often tested in this type of question. Because scientific experiments questions are usually longer to read than most other types, they are very frequently followed by more than 1 MCQ. As for previous types of questions, if the experiment is complex, the first question may be designed to assist students in understanding experimental design.
 

Problem solving

This type of question is often the most problematic as it requires to use complex and nonlinear thinking techniques. Questions often involve less context than for other types and are rather similar to thought puzzles. While an iterative hypothesis testing approach can sometimes be useful, lateral thinking is expected in order to find a logical approach to solving the problem in a timely manner. Solving a thought puzzle usually involves deducing information that is explicitly missing and requires overcoming mental set and functional fixedness. Often, a major premise will be given and a minor premise must be identified from the fractional or contradictory information described in a scenario.