2.2. El Registro de Propiedad Vehicular
2.2.3. Reglamento de Inscripción de Propiedad Vehicular 1 La Orden de Captura como “acto no inscribible”
2.2.4.1. Las Resoluciones del Tribunal Registral y los precedentes de observancia obligatoria
in Problem Solving
This chapter provides a nuanced look at student performance in problem solving by focusing on students’ strengths and weaknesses in performing certain types of tasks. The items in the PISA problem-solving assessment are categorised by the nature of the problem (interactive or static items) and by the main cognitive processes involved in solving the problem (exploring and understanding; representing and formulating; planning and executing; monitoring and reflecting). The analysis in this chapter identifies the tasks and skills that students master better than students in other countries do, after taking into account overall differences in performance.This chapter takes a more nuanced look at problem-solving performance by analysing how students interact with the test items. It focuses on performance profiles, rather than on performance levels, in order to identify each country’s / economy’s comparative strengths and weaknesses.
The PISA problem-solving framework defines a broad construct. Problem-solving competence in PISA encompasses success with different types of problems and the mastery of several distinct cognitive processes. This chapter analyses strengths and weaknesses in problem-solving by breaking down overall performance into success rates according to
broad types of tasks (Box V.3.1).1
Why are students from certain countries particularly good at problem solving? The analysis in this chapter identifies the tasks and skills that these students master better than students in other countries. In doing so, it highlights, for each country/economy, the specific areas of problem solving with the greatest margin for improvement, thus suggesting priorities for improving curricula and teaching practices to foster students’ capacity to solve problems in real life.
Box V.3.1. how item-level success is reported
PISA reports the performance of all students on the problem-solving assessment on a common scale, despite the fact that different subsets of students are administered different items, depending on the test booklet they receive. The item-response model that underlies the scaling of students’ answers makes it possible to aggregate students’ answers into an overall score even if each student sees only a subset of the entire PISA item pool (see Annex A5 and OECD, forthcoming).
While this approach has many advantages, it can potentially hide interesting differences in patterns of performance at lower levels of aggregation, i.e. on single items or on subsets of items. To explore these patterns, one must use the unscaled responses of the students who answered each item.
In this chapter, average percentages of correct responses are computed at the country/economy level. For each item, the percentage of correct responses is simply the number of correct (full credit) answers divided by the number of students who encountered the question (non-reached questions are counted as incorrect answers). The average percentage of correct responses on a particular group of items, or on the complete pool of problem- solving items, is then the simple average of item-by-country/economy percentages of correct responses.
On average across countries, the percentage of correct responses is a measure of the difficulty of items. By comparing the percentage of correct responses across two distinct sets of items, one can identify the relative difficulty of each set. By further comparing the percentage of correct responses across two sets of items and across countries, one can identify where the relative strengths and weaknesses of each country lie. For each subset of items and for each country/economy, the result of this comparison is reported as an odds ratio. Ratios equal to 1 for Country A, for instance, indicate that the pattern of performance across items is in line with the average OECD pattern of performance. Ratios above the value of 1 indicate that the items in this subset were easier for students in Country A than, on average, for students across OECD countries, after accounting for overall differences in performance across the test. A ratio of 1.2, for instance, indicates that full-credit answers within this subset were 1.2 times more prevalent than on average across OECD countries, after accounting for overall performance differences. Ratios below the value of 1 indicate that the items in this subset were, on average, harder than expected for students in Country A: the pattern of performance corresponds to a country-specific weakness on this subset of items.
What the data tell us
• Students in Hong Kong-China, Korea, Macao-China, Shanghai-China, Singapore and Chinese Taipei perform
strongest on problems that require understanding, formulating or representing new knowledge, compared to other types of problems.
• Students in Brazil, Ireland, Korea and the United States perform strongest on interactive problems (those that
require the student to uncover some of the information needed to solve the problem) compared to static problems (those that have all information disclosed at the outset).
The remainder of this chapter discusses in more detail the two main framework aspects (the nature of the problem situation, and problem-solving processes), and compares the performance profiles of countries within each aspect. It also links the framework aspects to skill demands and derives implications for teachers and curriculum developers.
frameWorK aSpectS and relative SucceSS of StudentS in each area
The PISA problem-solving framework provides the basis for the analyses in this chapter. The framework was used to develop items that vary by the nature of the problem situation and by the particular problem-solving process targeted (see Chapter 1 and OECD, 2013). Together, the 42 items included in the test, which also vary by problem context, by difficulty and by response format, are representative of the problem-solving domain as defined in PISA. The problem- solving proficiency scale summarises overall performance on the test. Instead of focusing on the overall proficiency in problem solving, this chapter analyses performance on subsets of items in order to identify systematic differences, across countries, in students’ success in handling different families of tasks.
The PISA 2012 problem-solving framework organises the domain around two main aspects. A first important distinction among problem-solving items is between interactive and static items; this is referred to as the nature of the problem situation. A second important distinction between items is related to the main cognitive processes involved in problem solving. Each process is defined by a pair of verbs: exploring and understanding; representing and formulating; planning and executing; monitoring and reflecting.
Figure V.3.1 presents an overview of the classification of items according to their characteristics. A statistical analysis2
confirms that the test was constructed so that there is no strong association between the main cognitive process involved in the task and the static or interactive nature of the problem situation. As a consequence, strengths and weaknesses in particular cognitive processes are unlikely to influence strengths and weaknesses that are found in interactive or static tasks.
•
Figure V.3.1•
number of tasks, by framework aspect
Problem-solving process