2005

Temenoujka Fuller

A Map of Students' Learning Demand and Learning Orientations

    The goal of this study is to present the dependence of students' learning demand and students' personal learning preferences. To achieve this goal, 51 community college students with low achievement of placement test were surveyed by the Learning Orientation Questionnaire developed by Martinez (1999). The data about students' learning orientation is presented in Table 1.

Scores	Range	Number of students	%	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).       

The community college sample has 25% more conforming students compare with the University students [2]. The average for University students is 16% higher in the direction of transforming students.

The vertical coordinate (OY) on Fig. 1 represents the difference between student's learning orientation score and the average for the group (learning orientation variances). The learning orientation value is positive if the student's score is above the average, and the learning orientations appear as negative if the individual score is under the average for the group.

    The learning demand is a two dimensional coordinate (Fuller, Abram, and Dishlieva, 2001), measured by the day of visit (OX) and the total time of visit (OZ). 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' visits at the learning center were traced during the first seven weeks of the spring semester in 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 for each individual student is presented on the third axis (OZ) which is perpendicular to the page.

Students' learning demand is also divided in two layers for better visualization. Above the "see level" with different yellow colors are presented 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 hour the learning center is overloaded. It is interesting than the yellow areas become absolutely solid during the midterm at the end of the period of observation.     

    Students with Learning Orientations below the average (negative OY values) are more active at the end of the semester compare with the students with learning orientation scores above the average (positive OY values). The pick in so-called conforming students (highest negative score for Learning Orientation) is the "Mountain" area circled and labeled as "Fear of Failure". Not only that dependent students need more tutoring and learning services, but also they are motivated by fear and learning anxiety. To avoid fear, educators need to break the actions leading to fear - procrastination, late visit of the learning facilities. At the same time, students with more global and transformable behavior use the learning facilities on time. The important finding of this study is that transforming students do not need supervision - they are ready for independent study. The second finding is that conforming students need guidance and supervision. The key discovery is that we can not guide and supervise students the same way.

    The study provides research questions about learning orientations and tutoring:

Do the students with Learning Orientation above the average with more than one standard deviation have natural hope of success guide?

· Are transforming students naturally more active at the beginning of the semester compare to the performing students?

· Will transforming students benefit from help oriented towards their personal strategic planning?

· Do they need to help with the global picture or challenge with the detail of different elements of the learning task?

Further, 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 (64% about the average). According to Martinez (2003) those students are performing. The research questions for those students are:

• Do the performing students benefit the most from learning services with more common sense examples, allowing them to try problems on the tutoring white board with very little help when needed?
• Do the performing students benefit more than the rest of the students from well defined negotiable objectives?
• What would be the best method for using technology with performing students?

Finally, the conforming students are no more than 20% to 30% of our study; however, they are the most difficult customers for the learning center. The research questions for performing students, emerging from the study are:

• How to address in the most constructive and optimistic manner students' actions leading to fear of failure;
• How to utilize the natural attempt of performing students to get help at the last minute, by helping them in the last minutes and planning for the future?
• The limitations of this study have different character. First of all, the students in this study were with almost mono-cognitive profile (30 to 40 percent at placement tests), which should not be generalized for the population of all students enrolled in developmental classes. The role of tutors' expertise and tutors' 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 is often 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 reasons 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 connection 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.

    At the beginning of the semester, learning demand is considered active. Students' learning demand

When the students are under the pressure of the midterm (day 40 in the seventh week of Fig. 1) 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 with scores between these two groups have almost equally distributed learning demand throughout the entire period of observation.  However, most of the students are in the middle area (plus or minus one standard deviation from the mean). Students with learning orientations in the intermediate area are the majority of students using the learning center. The "group" of intermediate students in terms of learning orientations is well supported by the learning center and probably those are the "beneficiary" students in the system of old teaching paradigm. One important question is: How students who like semi-structured material will be affected in the new paradigm? The results of this study lead the researcher to a conclusion, that teachers in the old paradigm have developed intuitively successful method for the majority of the students.

    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 in the time of changing of learning paradigm?

    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.

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References

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. 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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