Causal attribution of school success investigated by Q-methodology

Kristína Žoldošová, Pavol Prokop

 

 

 

The existence of intrinsic motivation in learning is a reflex of unsatisfied needs of knowing. Essentially, it is needful to transfer learning responsibilities from a teacher to a pupil. Besides responsibility for her or his own education, the pupil should have the abilities of self-control, self-evaluation and self-regulation. Pupils loose their feeling of freedom when teachers use a  teaching method that is based on giving strict and exact instructions for pupils in their school class-work. The result is that after time they are not able to carry responsibility in their own education process and control of one’s own thinking and behavior.  By responsibility we mean the ability to make one’s own decisions and by control we mean ability to make effective decisions.

One of the unwritten rules in education is to change pupil evaluation to pupil self-evaluation. The correct perception of one’s own abilities (ability of own education self-control included) is a basis for this change. We have to think about the perception of the causalities of school success level and also in case of the failure of transferring the causalities. The issue of the described change is complicated in many ways. The teacher's role to help pupils to develop self-understanding and the role of creating a considerable learning environment are inevitable elements of effective education. A unique set of qualities and abilities of each pupil is another aspect that is asking for an acceptance in a suitable educational environment. Using the comparative method while the pattern of comparison is developed by the personality itself develops life-long self-confidence. Society is an inseparable part of the pupil’s living environment. That is why we have to include its influences to the development we have just described. The result of including these influences in this way is that every pupil is comparing their own level of school success with set "standard" created by observing their own successes measured against that of their schoolmates.

As we are comparing the preferred type of motivational process at school we can easily find out that the presently preferred extrinsic motivation in achieving school success is not the right one that could lead the pupils to effective self-control of own school success. Intrinsic motivation flows from internally created incentives and asking for pleasurable work and effort that leads the person to achieve the desired destination, target, or benefit. The extrinsic motivational process is strictly oriented to achieve benefits that flows (as well as incentives) from the external environment.

The value of intrinsic motivation in the learning process is undisputed (the statement is based on basic characteristics of intrinsic motivation). The complexity of intrinsic motivation is completed by previous learning experiences, concretely a ratio of one’s own school successes and failures. Pupils are continuously re-evaluating their  own abilities used at school, mostly by watching success of the schoolmates at the same level.

The main tools used for increasing self-confidence:

·        opportunity of making own decisions,

·        increased level of responsibility,

·        consciousness,

·        valued personality,

·        appreciation of effort,

·        assurance that other members of the peer group the person belongs to are accepting him/her nearly by the same way how he/she accepts him/herself.

On the other hand, main factors that lead to decreased self-confidence at school are:

·        underestimating,

·        overestimating,

·        strict external behavior control, forcing to higher efforts,

·        pressure of external expectations (mostly from teachers and parents),

·        limited independence,

·        contempt  of pupils needs,

·        expressing their imperfection in comparison with adults (Helms, 1996).

 

Perception of one’s own capabilities highly influence the whole attitude to life and directly influences character of prior motivation as well.

Perception of one’s own capability at school is described by a few different theories. We prefer the explanation given by causal attribution theory.

 

Causal attribution theory

In this theory, the greatest influence on a pupil’s school success is not in real reason that caused result of the situation but preferred attributions of school success. It means that what a pupil believes has caused the resulting situation has a stronger influence on further learning successes than a certain success (or failure) by itself. For example, a pupil can believe that he/she failed a math exam because he/she has spent not enough time in preparing for the exam, but can instead think that the teacher was not fair (or not objective) in the test evaluation, not that he/she doesn't have abilities for learning math. Every one of these mentioned attributes will influence the quality of preparation for further math tests in a very different way.

Weiner (Spaulding, 1992) defined 4 basic attributes of school success: abilities, effort, level of task difficulty and luck. We can sort these attributes in different categories. One very useful sort is to sort by external and internal attributes. The internal ones are connected with some pupil character phenomena and external ones are connected with any part of the environment. By this description we can say that abilities and effort are internal attributes because they are directly connected with the personality (described, for example, by pupils statements like, “I am good in math. I have worked hard to get the good test grades!”). Task difficulty and luck are external attributes.

Another type of attribute sorting is by judging its stability. We can recognize stable and unstable attributes. Stable ones are independent of time and circumstance. Unstable ones have opaque characteristics. To categorize stable attributes, we can sort it according to ability attribute and task difficulty attribute. Effort and lack are unstable attributes.

Attributes can be controllable and uncontrollable. The criterion is about willful influencing of an educational situation by leading it to wanted targets and the ensuing results. Just effort attribute is a controllable attribute, while other ones are categorized as uncontrollable attributes. If a pupil's preferred attribute is ability or effort (internal attributes), we can expect a higher level of future success in similar situations. By experiencing success, self-esteem and self-confidence increase and there is a very tight connection of this phenomena with intrinsic motivation orientation in solving similar situations.

Pupils ought to aim at internal attributes. Teachers have a great role in leading pupils to get this state. The teacher would point out that not enough effort can lead to eventual test failure. Effort is the only internal, controllable attribute of school success. That is why it is the most suitable attribute for a pupil’s positive cognitive development.

 

The research aims

We wanted to observe possibilities of attribute preference changes. We realized the research in science education by changing its typical educational environment. We wanted to build an environment full of natural incentives for understanding nature, incentives of science education motivation. Therefore we established a science education center in the field. We prepared science education courses based on observing activities right in the field and investigations of natural objects and phenomena using experimental activities in a field laboratory setting. Pupils are learning by using their own experiences with observed and investigated nature. Information acquired this way is more useful and more stable than information acquired by passive learning realized in a traditional science classroom, where a teacher is the only source of information.

We were trying to put in a new established science education environment as much natural learning incentives as was possible for causing growth of intrinsic motivation for learning science. We did not choose research fixation to causal attribution of school success at random. It resulted from theoretical analysis of motivational processes of science learning side-by-side with positive ways of “learning-by-doing” method realized right in the field. Science learning at the center in the field is based on experience learning and we expected that this kind of learning environment will influence causal attribution of school success. Pupils that will graduate the science learning course in the center will prefer controllable attributes of school success unlike pupils in the control  group where we expected preference of uncontrollable attributes of school success. This would be great change in the whole motivational process and it would deal with the problem of well known (or the greatest one) problem of pupil’s boredom and lassitude at school.

 

Research methodology

For investigation of this phenomenon integrated into opinions and attitudes we chose q-methodology.

Opinions and attitudes are seen as complex entities. They are synthesized internally often in illogical and idiosyncratic ways, and they represent the conceptual framework of the context of each individual's own experience. They form over long periods of time and occur wholly within each of us. The research goals supported by Q-methodology are to focus on discovery and understanding of individuals as complex, holistic beings (Wigger, Mrtek, 1994). Q-methodology is an intensive methodology that permits researchers to map the attitudes of a set of respondents toward some issue under study (Durning, Osuna, 1994; McKeown, Stowell-Smith, Foley, 1999).

With Q-methodology and by-person Q-factor analysis it is possible to measure arrays of attitudes at a certain point in time or measure attitudinal changes over time. Q-methodology is most appropriate for use in situations where available scales seem inadequate, where the theoretical framework of a research problem is not well understood, or when the research subject deals with inherently subjective issues such as likes, preferences or agreements.

Q-methodology approaches opinions and attitude research using both quantitative and qualitative research paradigms to its advantage. Opinion research is most often performed entirely within the qualitative paradigm (using interviews and questionnaires). Qualitative methods are useful for discovery and exploration (Mrtek, Tafesse, Wigger, 1996).

The main principle of q-methodology is compiling of a statement set. The statements characterize the investigated topic from different views. Before compiling the stimuli statements we needed to clearly identify and define the main problem to be solved (investigated phenomenon). The validity of finally created research tool flows (by main part) from very well elaborated statement set. There are two important criteria for statement creation: 1) the stimuli statements were to express the fullest possible range of cell characteristics and 2) stimuli statements had to be readily understandable (Durning, Osuna, 1994).  Every statement is written on a separate card and individuals are usually asked to sort the entire set of pre-written statements regarding a complex subjective topic using some condition of instruction. Statements are ranked among 7 - 11 piles along a predetermined continuum from "most agree" to "most disagree", with a distribution midpoint equivalent to indifference or ambivalence (Mrtek, Tafesse, Wigger, 1996). How participants sort these statements along a continuum of valences ranging from extreme disagreement to extreme agreement communicates their "operant subjectivity" at the time of the administration (Durning, Osuna, 1994).

Individuals do not rely on verb-vocal reports to describe their experiences insofar as they can use objects, pictures, recordings, and gestures as symbolic and self-referent forms of communication. It means, that if it is needful, we can use objects, pictures or other different stimuli instead of written statements on cards (Taylor, Delprato, Knapp, 1994; Brown, 1996).

The number of the cards with statements should be between 60 and 140 to retain statistical stability and reliability of the created research tool. A very good scale has about 60-90 statements.

If, for instance, the research tool has 60 statements, after reading them all, the respondent can set them up by his/her attitude toward the problem defined in the statements (from highly positive attitude to very negative attitude). However scoring of responses is very difficult in this type of set-up. That is why it is possible to use different types of the statement sorts. The respondent can choose how many different values he will assign when he will set up the statements. Or, we can set the number of values and respondent will set up the same or not the same amount of statements assigned to each value. In this case we will choose sort with not the same amount of statements put to different defined values, we limit the respondents in their attitude expression. But from the view of statistical interpretation, this sort has more advantages than sort with the same amount of statements put to different values. The amount of statements put to different values is adjusted to quasi-normal distribution (gauss curve). The most statements amount is assigned to the middle value. Continuously to both ends of the value distribution, the number of statements decreases. It means that respondents assign few statements to very high and very low values and more of them to the neutral value. We can say that respondent’s attitudes are more visible.  The display of sorted statements will follow the pre-selected quasi-normal distribution, for example, like this:

 

Table 1: quasi-normal distribution of q-statements

 

value assign to statement

0

1

2

3

4

5

6

7

8

9

10

amount of statements assign to value

2

3

4

7

9

10

9

7

4

3

2

 

Statements of high salience with which the sorter has strongly agreed and strongly disagreed will be placed at the extreme ends of the sort pattern. Statements which hold little salience for the individual will be found near the midpoint of the competed sort (Mrtek, Tafesse, Wigger, 1996).

The task for respondents is to read all 60 statements. Then they have to choose just two of them with the highest agreement and two different ones with the greatest disagreement. The first two ones will get a value of 0 and the second two a value of 10. Then the respondents have to continue this by setting up the statements by the pattern (presented in the table) and to value number 5 they can put statements to which they do not have clear positive or negative attitude along with the statements they do not understand. The middle value number 5 is called neutral, because by assigning a card to this value, the respondents do not express their attitudes to the statement.

By sorting the cards with statements we will get a continuum from the respondent’s highest agreement to the highest disagreement to the problem put in the statements. If we assign the cards with numbers and in which cards with low numbers will represent statements with positive attitude toward the problem and cards with higher numbers will represent statements with negative attitude toward the problem we can present respondent's attitude by a graph. The X-axis represents the cards with statements and Y-axis represents assigned statements. By the rise or fall of the graph slope, along with the intensity of the slope, we can judge global attitude of the respondents toward the investigated problem.

Q-methodology can be used for individual qualitative research or group qualitative research. A potential disadvantage of the method is that it is not possible to use it for larger respondent groups. In this case, we investigated a group of respondents, creating a graph that presents the results of q-sorting arithmetical average of values assigned to individual statements. Every average has to be described by its standard deviation. Statements with a very high standard deviation not representing the attitude of the whole group can lead us to misinterpretation of the results. High standard deviation means non-homogeneous attitude of group respondents to the statement.

Matching or not matching sorting of the statements between the respondents can be expressed by counting correlation coefficients. It means, first, the Q-sorts of respondents are inter-correlated. The correlation coefficient between two sorters indicates the extent to which viewpoints are similarly expressed by the Q-sorts. In this way we are trying to find a measure of equality in assigning the values to the statements between two respondents. Then we form a correlation matrix. Example:

 

Table 2: inter-correlation matrix of Q-sorts

 

a

b

c

d

a

-

0,92

0,08

0,08

b

0,92

-

0,17

0,17

c

0,08

0,17

-

0,75

d

0,08

0,17

0,75

-

 

 

The inter-correlation matrix of Q-sorts is then subjected to by-person factor analysis wherein persons are considered as variables and the separate statements as stimuli (using factor analysis depends on research character, it is not used in every case of Q-method usage). The factor analysis procedure identifies groups of individuals with similar viewpoints (Mrtek, Tafesse, Wigger, 1996).  Then the factor matrix is created. The factor matrix summarizes which of the Q sort are similar or dissimilar from one another.

Results interpretation is very simple. Respondents a and b sorted the statement cards by very similar way, because the correlation coefficient is relatively high. A low correlation coefficient between two respondents means that the respondents sorted the statements in a very  different way, their attitude toward the problem is different. By creating and evaluating the correlation matrix we will get two (or more) respondent groups that are different in their attitudes toward the research problem (different by sorting the statements).

If all respondents sort the statements in nearly the same way, then the correlation coefficient among all their sorts will be high and only one factor (viewpoint) will be isolated. On the other hand if there are three groups of people consisting of individuals in which the inter-group correlation are low and intra-group correlation are high then a three-factor solution will have resulted. The number of factors simply indicates how many different viewpoints exist among the people making the Q-sorts (Mrtek, Tafesse, Wigger, 1996).

For presenting the results we used tables and graphs. In continuity with the collected data character we used (except the mentioned arithmetical average, standard deviation and correlation coefficient - Pearson's) parametric t-test for resolution of values averages assigned to statements by respondents of experimental and control group (before using t-test, normality test was used).

Statistical analysis used in Q-technique is concerned with populations of statements rather than populations of people. This implies that sample sizes are defined statistically in terms of the number of statements to be sorted rather than the number of respondents making the sort. Q-methodology needs only a small number of persons making the sorts. It is important to know that Q-methodology reveals how many different viewpoints are present among the group of respondents, but it does not show how many people exist in the population who have a specific viewpoint (Mrtek, Tafesse, Wigger, 1996).

It is a powerful and highly flexible tool to help researchers understand and identify subjective opinions in a systematic and objective way. It can be used to assess opinions among individuals in groups of persons at a certain point in time and/or to measure changes in those opinions over time. Q-technique can be used equally well to demonstrate the range of opinions and viewpoints expressed by a single individual under different conditions of interest, thereby providing opportunity to study the effect of conditions on human subjective expression. This is how we used it.

The statistical analysis could be elaborated using special software. For instance, McKeown, Stowell-Smith and Foley (1999) used "PCQ program for Q-technique", Steven Brown (1996) suggests to use  "Q-Method program" available in IBM, VAX and UNIX platforms.

 

Respondents

All the respondents are primary school pupils, 7-14 years of age. The experimental group is compiled of 81 respondents, the control group of 50 respondents.

 

Results

As we used the q-methodology for investigation special phenomenon of causal attribution in continuity to school success we needed to adjust the method to the problem of the research. As we mentioned previously in the research theory, we can find four different attributions of school success. One of them is controllable, effort, and the remaining three are uncontrollable - abilities, task difficulty, luck. We compiled the statement set of 60 cards. 15 of them characterize each one of the causal attributions. We numbered them in this order: 1-15 effort, 16-30 abilities, 31-45 task difficulty, 46-60 luck. If the respondent will assign q-statements numbered 1-15 with high values, we can see it in a graph result presentation like decreasing tendency and we can say that the respondent inclines to controllable causal attribution of school success. If the graph will have increasing tendency, respondent prefers uncontrollable attribute of school success.

The cards contain statements from different facets of school work (learning style, teaching style, evaluation of school success, social part of class environment, testing, examining of knowledge, attitudes to teachers, attitudes and relations toward schoolmates, etc.) because creation of the attributes is conditioned by various factors (a complex summary of attitudes, pupil’s opinions, based on a pupil's experiences). In this case, its quite clear that we cannot put all the factors that contributes on attribute creation to limited amount of the statements. The compiled statement set we use in our research is in Appendix 1.

Every respondent assigned every statement a value of 0 to 10 by measure of his agreement or disagreement with the statement. The highest agreement means an assigned value of 10. We are using not just this horizontal sorting of different values, but vertical sorting as well. The vertical sort leads respondents to put limited number of assigned cards to the assigned values. We are forcing the respondents to "crystallize" their opinion. If we do not using vertical sorting, they could put all the cards in a neutral or nearly neutral value and we cannot find in this kind of result what we are looking for. By forced vertical sorting we are trying to identify at least small divergence in attitude of the statements.

For each statement we have got one value (from 0 to 10) per every respondent of the experimental and control groups of students. Then we ordered the statements by its respective numbering. The cards were marked by the number on the back side of the card, so the respondents cannot be influenced by our numbering in statement sorting.

We evaluated the sorting for each group separately. For each group and each statement we counted arithmetic average and standard deviation. Then we graphed the results. By the graph tendency we can judge group attitude toward the problem. We can find which attribute is preferred in which pupils group. Except finding the most preferred attribute in the group we can assess significance of the attitude. By the set hypothesis the graph experimental group would have decreasing tendency (higher values of statements that are characterizing controllable attribute - effort, than statements that are characterizing non-controllable attributes) and the graph of control group would have increasing tendency. By this result we can see a change of causal attributes preference and influence of used method of learning by doing to attitudes toward science education. By the explained theory it can mean shift from extrinsic motivation preference to intrinsic motivation.

 

Graph 1: Q-sorting of statements in experimental group (n = 81)

Graph 2: Q-sorting of statements in control group (n = 50)

 

As we can see by comparing results presented in the graphs that the experimental group prefers controllable attribute of school success, effort, and control group oscillates somewhere between non-controllable attributes of task difficulty and luck. All respondents show similar attitude to internal non-controllable attribute, ability.

Tendency of the graph is more visible in graph 1 (experimental group) than in graph 2 (control group). We can say from this that values of the statements in graph 2 are near the midpoint value, but we can see a light increasing tendency - lower values for statements that are characterizing effort and higher values in statements of task difficulty and  luck. In graph 1 is the tendency decreasing, higher values for statements that are characterizing effort and lower values for non-controllable attributes (especially luck).

The difference of the statements valuation between control and experimental pupil groups was tested by parametric t-test. The results are in Table 3. Values assigned to statement No. 58 do not have normal distribution in the control group. That is why we could not test the difference of the arithmetical averages by t-test. We found out significant differences between arithmetical averages for 15 out of 15 statements that are characterizing controllable attribute of school success, effort, for 4 out of 15 statements that are characterizing non-controllable attribute abilities (the lowest level of differences - similar attitude of control and experimental group), for 10 out of 15 statements that are characterizing non-controllable attribute task difficulty and for 13 out of 15 statements that are characterizing non-controllable attribute abilities of school success, luck.


Table 3: Significant differences of statement valuation between control and experimental pupil groups

 

effort attribute

statement

testing parameter t

1          

3,78664E-26**

2          

4,39312E-13**

3          

1,47375E-09**

4          

1,28997E-16**

5          

2,19301E-06**

6          

1,27144E-08**

7          

2,85416E-05**

8          

8,52334E-19**

9          

4,13602E-07**

10       

4,78116E-08**

11       

7,30372E-17**

12       

3,42383E-08**

13       

0,000107838**

14       

6,7777E-07**

15       

4,44364E-10**

 

abilities attribute

statement

testing parameter t

16       

0,109464326

17       

0,088858795

18       

0,048200035*

19       

0,345326557

20       

0,24316621

21       

0,002703243**

22       

0,544769374

23       

0,395753123

24       

0,016920559*

25       

0,408860656

26       

0,365722375

27       

0,240486619

28       

0,196074273

29       

0,008516152**

30       

0,071759467

 

 

 

task difficulty attribute

statement

testing parameter t

31       

1,08038E-07**

32       

5,96265E-05**

33       

0,656589799

34       

2,13582E-12**

35       

0,000182617**

36       

0,08640873

37       

0,02548505*

38       

0,000282639**

39       

0,000979273**

40       

0,577203314

41       

2,09505E-07**

42       

0,001418398**

43       

0,145346317

44       

0,810214191

45       

2,52015E-05**

 

 

 

 

luck attribute

statement

testing parameter t

46       

6,07283E-08**

47       

1,37483E-05**

48       

0,00568137**

49       

0,846856925

50       

0,643058795

51       

9,89462E-05**

52       

1,77504E-11**

53       

4,66657E-09**

54       

3,40021E-05**

55       

0,001817681**

56       

3,15889E-08**

57       

1,14041E-11**

58       

-

59       

0,004184783**

60       

7,2106E-10**

 

Finding a level of respondent groups conformity (homogeneity of expression) was investigated by using the Pearson correlation coefficient. Considering the number of respondents, we cannot present the correlation matrix here (that would have parameters: 131x131). We found out the highest correlation within the experimental group, a lower level of homogeneity exists in the control group and very low correlation exists between the experimental and the control group.

By evaluating these correlations, we confirm the results gained by graphical presentation.

 

Discussion

On the basis of the presented results, compared with the graphical result presentation, we can claim, that pupils from the experimental group assigned significantly higher statements, that are characterizing the controllable attribute of school success, effort, in comparison to the control group. On the contrary, statements that are characterizing the non-controllable attributes, task difficulty and luck, are significantly higher valued by pupils from the control group. Very low difference is in attitude toward attribute ability.

To find out more details about the character of the difference in the attitudes we order the statements by the decreasing arithmetical averages (graph 1 and graph 2). By reading statements with the highest and lowest values for both respondent group we can find out some more information about the attitude toward the causal attribution of their school success.

We discovered these differences by our analysis of the collected data. Most pupils from control group think that most reasons of their school failure are coming from the environment, conditions, circumstances they are in. These factors they cannot influence, that is why we call them non-controllable attributes. They used to attribute the reasons for failure to teacher injustice, luck, or difficulties of tasks. They are not used to carrying responsibility for their knowledge development. Its not the fault of the pupils, it is fault of the education system that allows pupils to develop this state of thought. At school, the teacher usually accepts responsibility. They pupils think that insufficient effort is not a valid reason for failure in school. When they are successful, they assign the reason for their personal success to their own abilities (for example, they say that good marks they have just in subjects they are able to learn), but also to luck (for example they say, that teacher usually do not examine them when they are uninformed; or, that they usually get the easier tasks on tests, etc).

On the contrary, the experimental group inclines to the effort attribute. Good marks and teacher satisfaction are good benefits for them. They are able to esteem themselves, and have the ability to feel their own abilities at the right level. They feel their own ability to influence their further level of school success, the ability to learn and to use the learned knowledge.

The lowest values were assigned to statements that are characterizing the luck attribute. They do not rely on unstable and random situations. More they are aimed at situations they can influence by their own will and own behavior and to direct the situation to their success. Even in case of failure, they usually don’t give up. They know that the failure is usually the result of not enough effort. This can be changed in the future, because it is matter of their willing and nothing that they cannot expect or influence. They feel their own competencies for influencing their own performance. By valuing the statements we can see a great difference in the critique of the school environment . The experimental group shows trust and confidence in teacher and the entire school institution. The control group feels more injustice at school, the most of it in the teacher’s personality.

The control group has opinions to causal attribution of school success less homogeneous, while in the experimental group we can find quite a high level of  homogeneity. Respondents of the control group came from different educational environments and respondents that took the course of science education in the field were influenced by the same environmental method. That is why we could find such a high level of homogeneity in their expressed opinions. We noticed the difference in homogeneity resulting from the changed attitude toward causal attribution of school success was caused by influence of used method in the Center of science education in the field (learning by doing right in the field).

 

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Appendix: Statements used in q-methodology that characterize the attributions

controllable attributions:

attribute: effort

1.      Good grade at school depends just on measure of my effort I put to preparation.

2.      All tasks given by our teacher like homework I am trying to elaborate alone and when I am not successful I am asking my parents or schoolmates to help me.

3.      Sometimes it happens, that I don't get good grade even I was learning the topic. In this case I know that I put not enough effort to the preparation for the lesson.

4.      Behind good grade I can see my effort and it's giving me energy for further learning.

5.      When I am not learning I am always punished by bad grade.

6.      When I have got bad grade I have strong regrets why I didn't dedicate more time to the preparation.

7.      When I have god bad grade I am so sorry that immediately I am trying  to improve the bad profile at school.

8.      I know that behind strong effort there is always good grade.

9.      I know, that my teacher is disappointed when I am getting bad grades, that's why I am trying to improve it.

10.  The greatest punishment at school is getting bad grade for not enough good preparation for lessons.

11.  The best benefit of learning effort at school is getting good grade.

12.  I am so glad, when I get better grades on tests and exams compared with my schoolmates, because I use to do all homework.

13.  I like when teacher notices and values my effort to bring some materials to school class or when I am asking some questions I am interested in.

14.  I like the possibility of asking questions, because just teacher can advice me by the best way what and how to learn to be successful

15.  I like when teacher is able to accept some reasons of not enough preparation for lessons, in a case of my apology. Than I am trying to learn it as soon as possible and I want the teacher to know that I have just learnt it.

 

uncontrollable attributes:

attribute: ability

1.      Bad grades I can get just in subjects I have no abilities for.

2.      When I have to answer teacher's questions in front of all the class I am always afraid, even I know that I learnt the topic.

3.      I have bad grades just because I am not able to express my thoughts very well.

4.      Even I am learning the subject I can get bad grades because my teacher does not believe that I can know it better.

5.      It happens quite often that I  don't understand teacher's question.

6.      I get bad grade when the teacher forces me to solve tasks that are over my real abilities.

7.      Teacher usually gives me very difficult questions an I am not able to deal with them.

8.      The greatest disappointment is when I am preparing myself for lessons, but teacher gives me so difficult tasks for solving that I need much more knowledge to do it.

9.      I don't like doing tests because there is such a short time for the solving that I cannot do it so quickly.

10.  The worst evaluation situation is when the teacher asks me questions and require the answer immediately.

11.  I am not able to be concentrated to tests.

12.  When there is very important test, usually I am in so high stress, that I cannot be concentrated to do it well.

13.  On the class I usually don't understand what the teacher speaks about , that is why I am not able to do homework. For understanding I need more time.

14.  It seems that we learn too much topics on one lesson and I am not able to learn it out all.

15.  In some subjects I have good grades, because I am understanding the subject. That is why I have not very good grades in different subjects I am not able to learn.

attribute: task difficulty

1.      I use to et bad grades just because of injustice. Anytime we are doing some test I have the more difficult version of the test.

2.      Teacher tries to catch me that I don't know something I should know by giving me questions with not clear answer.

3.      If teacher gives us test before previous noticing, he/she is doing it because we made him/her angry and the test is very difficult.

4.      Usually when I don't know answer for teacher's question, other schoolmates wouldn't know it as well.

5.      Tests are usually very difficult because our teacher is not giving there tasks we have solved on the lessons.

6.      We use to have so much homework that I am not able to learn it everything.

7.      I like when teacher gives us easy questions, because than I am sure when I learnt that I will be successful in examining.

8.      If I have got bad grade just because of very difficult task I don't suffer for it so much.

9.      I like very difficult questions on test, because in the case I am not able to solve it it doesn't mean I am not good prepared.

10.  Good grade doesn't depends just on time I spent by preparation, learning, but it is highly dependant on task difficulty.

11.  I don't like verbal answering teacher's questions, because these questions use to be more difficult than task from writing test.

12.  I use to get bad grade just because I don't understand the question.

13.  I have got bad grade just when the teacher will ask me questions of matter I have learnt long time ago.

14.  The worst tests are the more important ones, because the teacher asks lot of topics of the subject we have learnt long time ago.

15.  If the teacher is not asking questions from older topics of the subject I will have just good grades.

 

 attribute: luck

1. I use to have luck for getting easier questions on tests.

2. I f I am not prepared for lessons and the teacher asks me questions, my schoolmates usually help me.

3. I use to get bed grades just by injustice way.

4. The teacher doesn't evaluate all schoolmates by the same way.

5. On tests I expect possibility of cheating.

6. When I am answering teacher's questions by verbal way, it's better like test, because i can easy change topic of speech when I don't know the answer.

7. In the case I couldn't prepare myself for next lesson I use to be very unlucky, because anytime it happens teacher will find it out for sure.

8. To do homework is not useful, because I can do it in break between two lessons.

9. I use to help teachers (to clean the blackboard, to borrow a pen...) and they will usually help me as well (on tests for example).

10. Sometimes I feel that learning at home is useless, because teacher will ask me just the one thing I didn't learn.

11. It's like bad luck that before very important tests I cannot be concentrated to the test preparation, because we have very much work at home or having important visit and so on.

12. Usually when I didn't learn teacher doesn't examine us.

13. Bad grades I use to get al subjects the teachers doesn't like me.

14. Good or bad grades depend mostly on teacher's mood.

15. At school I like the most my friends that are able to help me with any kind of testing or examination.

 

 

Dr. Kristina Zoldosova, PhD.

Assistant Lecturer at Department of Preschool and Elementary Education

Faculty of Education, Trnava University

Priemyselna 4

918 43 Trnava

Slovakia

kzoldos@truni.sk

tel:          +421-33-5516047 extension 529

 

Dr. Pavol Prokop, PhD.

Assistant Lecturer at Department of Biology

Faculty of Education, Trnava University

Priemyselna 4

918 43 Trnava

Slovakia