Student threshold

Introduction

"Real learning requires stepping into the unknown, which initiates a rupture in knowing..." [1]
It has been a concern to many University teachers why certain students "get stuck" at particular point of their education whilst others grasp knowledge with comparative ease. What might account for this variation in student performance and what could teachers do in order to help students overcome such barriers to their learning? As students from a wide range of educational backgrounds enter the University, the problem of threshold is becoming of increasing importance across all disciplines [2].

 

Students are challenged within a discipline when they don't see the relevance of subject to other areas of engineering and life sciences [3]. As it was previously reported by Cousin [4]: "First student: I understood it in class, it was when we went away and I just seemed to have completely forgotten everything that we did on it, and I think that was when I struggled because when we were sat in here, we would obviously got help if we had questions but... when it came to applying it...I understood the lectures and everything that we did on it but couldn't actually apply it, I think that was the difficulty." Therefore, students are lacking the motivation to gain insight course assignments, and later, are not able to translate their knowledge to other disciplines due to the previous surface learning. The essence of deep learning is understanding - true knowledge [4]. The term threshold concept denotes concepts that are essential to knowledge and understanding within the educational program or particular disciplines [5]. Threshold concepts act like doorways that enable students to comprehend a topic or an entire subject that they have not understood previously. The transformative nature of the threshold concept can create challenges to both students and teachers. Students may experience a threshold as a transformative process that is able to change student views on educational program or subject, integrative process that connects non-integrated ideas, irreversible process where the knowledge will remain for a long time and bounded process that refers to a subset of disciplines [6,7].

 

My personal teaching experience showed that every year students struggle with the obligatory master level courses. Certain students have difficulties with the programming using MatLab because they are unfamiliar with this software. Other students cannot remember basics of mathematics. The master program administration considered both student groups eligible for the course participation.  We know that there are always students which are exceptions e.g. lacking motivation, without clear educational goals, with different mental problems, etc. But, in general, I believe that it is possible to structure the whole master program in the way that students with their weaknesses and strengths will be on a similar level.

 

Threshold models

 

The application of concept mapping to university teaching has revealed the significance of knowledge structures in the process of student learning. Kinchin [8] reported two learning models, as shown in Figure 1.

 

Figure 1: Learning models (a) Chain model and (b) Network model [9].

 

Figure 2: Kinchin’s learning model [12].

The chain model shows a learning process as a single possible route from beginning to end, in which dialogue plays a minor role [9]. The chain model is understandable with the clear boundaries and defined responsibilities for students and teachers. In contrast to the network model, the chain model structure does not permit the further program development [10]. The network model includes more sources of uncertainty e.g. the nature of students' prior knowledge that requires teacher-student dialogue. The network model includes various routes without a clear start and end points.  In order to find a way to manage students with the different levels of knowledge and bringing them to the same start point and the same learning velocity, both models should be combined in one model, as shown in Figure 2.

 

The combination of chain and net models supports Norman's contention that "expertise lies in the availability of multiple representations of knowledge [11]. During the high-school and undergraduate studies, students establish a chain of understanding, whereas during graduate and post-graduate education, students develop and integrate nets of understanding that suits to particular contexts [12]. The chains might be also considered as competing. Net structures, which are focused on the integration of understanding, need to be explicitly connected to chains of practice. The understanding developed through the memorizing of information is integrated into a more holistic subject understanding, according to the development of knowledge structures from chains to nets. The combined model plays a key role in the learning process when we try to adjust a student threshold.

The threshold of knowledge refers to the boundary between "We know for sure" and "we don't know". If we want to come to the next step of our education, we have to go through the obstacles of threshold. In the master's program students obtain different levels of knowledge in dependency on the learning and teaching methodology of the bachelor studies. Certain students have learned only to memorize or to do a lot of routine practical work following the chain model, but other students used to learn through the discussion-based teaching and have already formed the interdisciplinary thinking. When students come to the master program, all of them have weak and strong knowledge in different spheres. Therefore, it is important to combine the practical and theoretical knowledge of their program in the course assignments. Students should have an equal opportunity to apply their strengths and weaknesses. At master level there is also a chance that students move from a core area of knowledge to pursue and specialize in particular spheres within a module. The explicit use of a threshold concept allows this process to occur within a coherent, wider "field" of study, whilst individuals may begin to investigate different subject areas and contexts the concepts ensure a level of coherence and allow a common point of contact for discussion and engagement with the work of others. In addition, both new insights and new knowledge can emerge.

 

 

What can we do about student threshold as teachers?

 

The information about prior student knowledge can be obtained from colleges or experience from previous years. The pre-test of student knowledge at the beginning of the course is an additional option to estimate how the teaching methodology, learning activities and assessment should be structured for the class. The first two-three weeks could be used for the repetition of the material which will be used in the main course. Repetition is vital to secure long-term memories. Spaced practice, mastery learning, repetition and homework (not at primary level) all give opportunities for repetition. Once new knowledge is understood, it can be safely learnt by heart as it will secure the links to prior knowledge. The spin model in the engineering is another option where 1-2 courses will be added to the master program, as shown in Figure 3.

 

Figure 3: Threshold concept in engineering using a spin model.

These courses will include assignments which are relevant to other courses in the master program. Spin is a well-known term given to rotation of a body. It has an influence across many branches of engineering, in fact almost anywhere where there is motion. Spin is a threshold concept because it explains and describes a lot of different types of motion and the understanding of spin is unlikely to be forgotten becoming a transformative and integrative knowledge. Once you understood "spin", you will use it in other subjects e.g. thermodynamics, chemistry, etc. Another option is to establish an introductory course at the beginning of master program where less simple assignments with narrower questions than in the mandatory course will be used. Such introductory courses will help students to repeat the information which they studied previously, and step up into the requirements of the mandatory course. The faculties will avoid situations when students cannot follow the course program and are not able to work on assignments and thus, the course level has to be lowed. These three options to adjust the student threshold will give an additional opportunity for both students and teachers to exchange the feedback, and create a "deep knowledge" platform for the participation in mandatory courses of the master program. When we talk about blended learning, we have all opportunities to use the digital tools for short quizzes, feedbacks and mi-term exams to influence the student threshold during the course time.

 

References

 

[1] Schwartzman, L. (2010) Transcending disciplinary boundaries: A proposed theoretical foundation for threshold concepts. In: Meyer, J.H.F., Land, R. and Baillie, C. (ed.), Threshold concepts and transformational learning, Sense Publishers.

 

[2] Rust, C. (2003), Improving Student Learning Diversity and Inclusivity, OCSLD.

 

[3] Worsley, S., Bulmer, M., O’Brien, M. (2011) Threshold concepts and troublesome knowledge in a second-level mathematics course. In: Hugman, A. and Placing, K. (ed.) Symposium Proceedings: Visualization and Concept Development, UniServe Science, 139-44.

 

[4] Cousin, G. (2010), Neither teacher-centered nor student-centered: threshold concepts and research partnerships, J Learning Develop Higher Ed, 2, 1-9.

 

[5] DeLotell, P.J., Millam, L.A., Renhardt, M.M. (2010), The Use of Deep Learning Strategies In Online Business Courses To Impact Student Retention, Am J Bus Ed, 3(12), 49-56.

 

[6] Meyer, J.H.F., Land, R. (2003) Threshold concepts and troublesome knowledge: linkages to ways of thinking and practicing within the disciplines. In: Rust, C. (ed.), Improving student learning and practice - 10 years on, OCSLD.

 

[7] Meyer, J.H.F., Land, R. (2005), Threshold concepts and troublesome knowledge (2): epistemological considerations and a conceptual framework for teaching and learning, Higher Ed, 49(3), 373-88.

 

[8] Meyer, J.H.F., Land, R. (2006), Threshold concepts and troublesome knowledge: issues of liminality. In: Meyer, J.H.F. and Land, R. (ed.), Overcoming barriers to student understanding: threshold concepts and troublesome knowledge, Routledge.

 

[9] Kinchin, I. (2009), A Knowledge Structures Perspective on the Scholarship of Teaching and Learning, Int J Scholar Teach Learn, 3(2), 1-6.

 

[10] Talbot, M. (2004), Monkey see, money do: a critique of the competency model in graduate medical education, Med Ed, 38, 587-92.

 

[11] van Heerden, A. (2005) Articulating the cognitive processes at the heart of chemistry. In: Riordan, T. and Roth, J. (ed.), Disciplines as frameworks for student learning, Stylos.

 

[12] Kinchin, I.M., Cabot, L.B. (2010), Reconsidering the dimensions of expertise: from linear stages towards dual processing, London Rev Ed 8(2), 153-66.