|
2005 |
A Decomposition of Students' Learning Demand and Learning Orientations
To find the dependence of students' learning demand and students' personal learning preferences, 51 community college students with low achievement of placement test were surveyed by a Learning Orientation Questionnaire developed by Martinez (1999).
|
Scores |
Range |
Number of students |
% of Total |
Community College Group |
Universities Group |
|
|
|
7 - 5.6 |
Transforming |
2 |
4% |
4% |
20% |
Transforming |
|
|
5.5 - 5.01 |
Hi Performing |
16 |
31% |
61% |
70% |
Performing |
|
|
5.0 - 4.51 |
Lo Performing |
15 |
29% |
35% |
10% |
Conforming |
|
|
4.5 - 4.01 |
Hi Conforming |
10 |
20% |
|
|
|
|
|
4.0 - 3.51 |
Lo Conforming |
8 |
16% |
|
|
|
|
|
3.5- 0 |
Resistant |
0 |
0% |
|
|||
|
|
|
51 |
100% |
|
|||
Table 1: Fifty-one community college students with almost the same results on standardized placement tests have different Learning Orientations (Copyright © 1997-2001, Margaret Martinez). It is obvious that the sample has 25% more conforming students compare with the University students [2]. The average for University students is 16% higher for Transforming students.
On Fig. 1, students' Learning Orientations are presented with a reference frame centered on the average values of the learning orientations for the group. The vertical axis presents the difference between students learning orientation score and the average for the group. The learning orientation value is positive if the student's score is above the average.
The learning demand (Fuller, Abram, and Dishlieva, 2001) is measured as total time invested by the same students in a learning center. All students, selected for the study, were enrolled into at least one reading, writing or/and mathematics developmental classes for which tutoring and learning cervices were provided at the learning center. The students visit at the learning center were traced during the first seven weeks of spring semester 2003. The days in the semester are the only time-variable which is different from part I of this study, in which the day and time of the visits is presented on each learning demand distribution. The reason that the time in the day is not presented is that the figure would be four dimensional. The learning demand (individual total time for each student) is presented on the third axis which is perpendicular to the page. Students' learning demand is also divided in two layers for better visualization. Above the "see level" are areas where the learning demand is more than one hour; in the blue areas, the learning demand is less than one hour. The map is designed to follow the ups and downs of students' learning demand as it depends on the time and students' personalities. The yellow areas are so called peaks in learning demand. It this peak hours the learning center is overloaded. It is interesting than the yellow areas become absolutely solid during the midterm.
Students with Learning Orientations below the average are more active before the midterm compare with the students with learning orientation scores above the average. The pick in so-called conforming students is the "Mountain" map as a "Fear of Failure" factor. Not only that those dependent students need more tutoring and learning services, but also they are motivated by fear and learning anxiety. For those students the scaffolding step-by-step tutoring will be beneficial.
Students with Learning Orientation above the average with more than one standard deviation, are motivated from the "Hope for Success." Those students are active at the beginning of the semester. Those students will benefit with help oriented towards their personal strategic planning. They need to "see" the global picture and the rest of the time will work on
Students with Learning Orientation under the average but above the lowers scores for the group have the most solid learning demand during the semester. It is interesting that they have peak on the area of the midterm. These students will benefit the most from learning services outside of the classroom. One additional advantage of addressing the second quartile group is that they are majority. These are the students who will benefit the most from different learning services with more common sense examples, allowing them to try problems on the tutoring white board with very little help when needed. In the project presented in part III, students from the second group will benefit more than the rest of the students. According to Martinez (2003) those students are performing. Technology is providing an important learning tool for performing students.
It is early to generalize the results for the dynamics of students' learning. First of all, the students in this study were with almost mono-cognitive profile (30 to 40 percent at placement tests,) which helps the research, but can not be applied for a random selection of any school. The role of tutors' expertise and ability are not discussed in this paper, but they are a significant part of a larger project.
The usage of an online tutorial during the researched period was traced for a subgroup of 9 subjects. The last research is not statistically reliable; however, the observations confirm the results presented in Johns and Martinez (2002). Students with low scores on Learning Orientation Questionnaire use online supplement as little as possible; students with higher scores on Learning Orientation Questionnaire use online tutorial frequently.
Case Studies
Only two cases with absolutely low scores on Learning Orientation Questionnaire were observed. According to the classification developed by Martinez (1999), those students are considered resistant. The observation conducted in this study showed that they are resistant to the regular classroom forms of education, but the same students are extremely enthusiastic in the process of learning in the learning center or online. One of the two resistant students, S_1, was more like the students who scored very high above the average. S_1 was independent learner, was using the online supplements far more frequently than the average usage for the group. The second student, S_2, was dependent learner with learning demand far below the average. The learning demand for S_2 was among the highest possible, or with other words, the student needed one-on-one or small group tutorials very much. While S_1 was independent student with high degree of computer usage, S_2 was dependent with low desire to use computers and high level of social learning skills.
S_1, one of the resistant students in the study, performed close to 100% in developmental math class, while the second student was suffering all the way through the community college classes. However, both students were enthusiastic learners. In a new learning paradigm, the educational system may consider those two students high level learners. Both students are willing to invest time to learn; however, their experience with the traditional school system are very negative. Why? The answer to this question is complex and exceeded the scope of this study; however, the luck of interest for students as individuals is one of the reason for this learning paradox. The best learners are not well situated into the system with teaching theory-of-use, or old teaching paradigm. Technology is not a solo solution for those students. The use of technology is more like a glue between dependent-independent divide of students' learning demand. Two forms of learning cervices are needed to address all difference of students' learning demand - fine touch of personal or small group tutoring, and high tech used as a tool to free students from the need to follow particular learning path and to address students' learning independence and a self-directed learning will of all individuals.
Fig. 1 Joint visualization of students' learning demand as it depends on students' Learning Orientations (Courtesy Dr. Martinez, 2003).
At the beginning of the semester, learning demand is considered active. Students' learning demand under the pressure of the midterm is considered passive or dependent learning demand. Therefore, the first part of the semester is divided in two periods due to the character of the learning demand. There are clear patterns of passive-active preferences at the top and bottom part of the map. Students with higher scores on Learning Orientation Questionnaire are active, while those with lowest scores are more passive. The students between them are with the least learning demand for those who scored above the average, and with the most equally distribute learning demand for those under the average scores on Learning Orientation Questionnaire. However, most of the students are in the middle area (the meridian or average in terms of majority). Students in this area with mathematically average Learning Orientations plus or minus have standard deviations for the group, as defined by Martinez (2005), are the majority of students using the learning center. These "group" of students is well supported by the learning center and probably those are the most productive students in the system of old teaching paradigm. However, there is a pressure for change of the paradigm or let us call it "theory-of-use".
The theory-in-use for the school system today is that teaching produces learning. The paradox is that we do not question this as far as students' grade fits the bell-curve and the teacher is accepted by the students. As educators, we need to openly and honestly ask a simple question: What are the problems with our teaching theory-in-use?
To address this question, a workshop on learning with technologies was developed and implemented by Fuller (2005). The workshop is guided by the discoveries of the most productive in asking and answering tough questions science, the science of modern physics. Modern Physics is not a subject in any school, usually modern physics is an appendix or, in some cases is a section or two at the end of the textbook. Teachers often do some supplements to illuminate some ideas (Fuller and Krumova, 2004), but mostly physics curriculum is focused on classical physics. One reason to use the discoveries of modern physics as a model is the fact that modern physics is that modern physics is most productive science in using technology and developing technologies to learn. Stated in terms of Argyris (1982), modern physics is a model for high level learning; in the high level learning or double loop learning, the theory-in-use is questioned and tested publicly. Questioning the tacit routines is the key to moving from teaching for Industrial Era to learning for Information Era.
Argyris, C. (1982). Reasoning, Learning, and Action: Individual and Organizational. San Francisco, Washington, London: Jossey - Bass Publishers.
Fuller, T. V. (2005). A Workshop on Learning, Technology, and Modern Physics [Long-running, multipurpose workshop]. Retrieved November 12, 2005, from http://pine.ucc.nau.edu/tvf2/
Fuller, T., Abram, M., & Dishlieva, K. (2001, August 17). Monte Carlo Simulation of the Learning Demand. Paper presented at International Conference on Numeric Calculation and Applied Mathematics, Plovdiv, Bulgaria.
Fuller, T., & Krumova, G. (2004). Online Reading Supplements for Atomic and Nuclear Physics Chapters of a General Chemistry Course. In Proceedings of the Scientific Conference with International Participation, Technical University of Varna, Varna: Vol. 3. Technical Edication (ISSN 1311-896X ed., pp. 653-662) Bulgaria: Technical University Varna.
Leach, J., & Scott, P. (2002). Designing and Evaluating Science Teaching Sequencing: An Approach Drawing upon the Concept of Learning Demand and a Social Constructivist Perspective on Learning. Studies in Science Education, 38, 115-142.
Martinez, M. (1999, November). Using Learning Orientation to Investigate How Individuals Learn Successfully on the Web. Technical Communications Online: Applied Research, 46(4). Retrieved February 19, 2005, from Internet: http://www.techcomm-online.org/issues/v46n4/full/0369.html
Martinez, M.. Supporting Individual Learning Differences. Retrieved February 19, 2005, from The Training Place: _http://www.trainingplace.com/source/research/customization.htm
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Last Updated - 11/19/2005