Recent Publication: John Martin & Anna Martin

John Martin, an Assistant Professor of Engineering Technology, published this article in June 2017 with assistance from Anna Martin of Kent State University.

Title: “Work In Progress: The Effects of Embedded-Formatting Applied to Statics”

Authors: John Martin and Anna Martin

 

Abstract:

Worked examples have been shown to be very effective in order to reduce cognitive load (Carol 1994), however there are many instances where worked examples may be ineffective. One instance is where a worked example may contain a number of unique pieces of information, each being incomprehensible to the learner in isolation, therefore the learner must mentally integrate each piece in order to understand the instructional material. A classic example of this is having a picture of a graph consisting of lines and then separately below having a list of equations for each line. There is a need for the learner to mentally integrate the two different sources of information, which asserts an increased burden on cognitive load therefore stifling the learning process. This is what is referred to as the split-attention effect (Sweller 1998). One way that has been shown to alleviate this problem is the use of embedded-formatting (Mayer 1990). Embedded formatting is where the unique portions of information are physically integrated with one another in order to reduce cognitive load. So, for example the graph with line equations described earlier could be shown where the equations are displayed on the graph directly next to the line that it is defining, so that the reader does not have to integrate the two mentally – it can be done visually.

Statics is typically the first core engineering course civil and mechanical engineering students take, therefore much of the information in this class is novel to the learner. Worked examples are often used in textbooks and are very useful, but they generally consist of a free-body diagram (FBD) and then a separate list of accompanying equilibrium equations for that specific FBD. This requires the learner to mentally integrate the two novel sources of information in order to make sense of the worked example, which can cause cognitive overload or an overload on working memory. This study will focus on identifying the effectiveness of using embedded-formatting with regards to engineering Statics worked examples.

For this study a quantitative quasi-experimental pretest-posttest study will be utilized to gain a better understanding of the effects of applying embedded-formatting to worked examples of Statics problems on student learning. Students within two separate engineering Statics courses will be considered, where the first groups/class will be given worked examples utilizing embedded-formatting and the second group/class will be given traditional worked examples as part of their instructional material. Additionally, a subjective measure of cognitive load will be used to quantify between group cognitive loads, while a posttest will measure student learning of the topic in general. The instructional technique will serve as the independent variable consisting of two groups; while the engineering concept knowledge of Statics, along with the subjective cognitive load scores will serve as the dependent variables to be measured using multivariate analysis of variance (MANOVA).

Recent Publication: John Martin & Anna Martin

Mr. John Martin, an Assistant Professor of Engineering Technology, published this article in June 2017 with assistance from Anna Martin of Kent State University.

Title: “Work In Progress: The Effect of Partially-Completed Worked Examples Applied to Statics”

Authors: John Martin and Anna Martin

 

Abstract:

Traditionally, instructional strategies used for teaching engineering subjects revolve around a scaffolded type framework, where problems are solved in-class by the instructor whom provides guidance to students that are simultaneously engaging in the problem solving with the instructor. This type of learning strategy is based off of a guided problem-solving approach. After a number of problems are solved in this manner the next step is usually to assign problems for the students to solve entirely on their own, taking away all the instructor support from the problem-solving approach. Research suggests that entirely removing all guidance too soon generally results in a situation where student learning must then rely on randomness. This is where the learning process is accomplished by randomly combining elements of information and then determining which combinations are effective (Sweller 2004), which is very inefficient.

This type of learning technique is very common within engineering subjects, as well as many other subjects and is based off of what is sometimes referred to as discovery learning (Bruner 1961). Research has suggested that making use of partially-completed worked examples can reduce cognitive load by decreasing the burden on working memory (Carrol 1994, etc.), in turn leaving more memory capacity to acquire knowledge. In partially-completed worked-examples learners are given a problem where certain portions of that problem are missing and they are required to fill in the missing steps. Implementing this instructional strategy can serve as a bridge between fully guided problem-solving and completely unguided problem solving. Adding the use of partially-completed worked examples to fill the gap between worked examples and independent problem solving has proven to be very effective in prior research (Paas 1992).

This study will examine the effectiveness of implementing partially-completed worked examples when directly applied to the field of Statics. This study will specifically examine whether or not the use of partially-completed worked examples create a more efficient and complete learning process when learning Statics.

We will utilize a quantitative quasi-experimental pretest-posttest study to gain a better understanding of the effects of partially-completed worked examples of Statics problems on student learning. Students within an engineering Statics course will be divided into two groups, where the first group will be given partially-completed worked examples along with traditional problems, where they are to solve the partially completed problems first and then the traditional problems afterwards. The second group will be given only traditional problems to solve. Additionally, a subjective measure of cognitive load will be used to quantify between group cognitive loads, while a posttest will measure student learning of the topic in general. The instructional strategy will serve as the independent variable consisting of two groups, while the engineering concept knowledge of Statics, along with the subjective cognitive load scores will serve as the dependent variables to be measured using multivariate analysis of variance (MANOVA).

Firm student understanding of fundamental courses such as Statics is crucial for their success in subsequent courses, and is also vital in providing solid background knowledge to appropriately comprehend more advanced topics. In order to maximize the learning process a clearer understanding of how the role of guidance during problem solving impacts student learning is necessary. This study hopes to shed light on the way in which instructional delivery impacts learning of engineering concepts.

Recent Publication: John Martin

Mr. John Martin, an Assistant Professor of Engineering Technology, published this article in November 2017.

Title: “Exploring Additive Manufacturing Processes for Direct 3D Printing of Copper Induction Coils – Symposium on AM: Novel Applications session.”

Author: John Martin

 

Abstract:

The production process of creating custom induction coils is often a tedious and time-consuming procedure, which is largely due to the fact that the coils are created by hand for the most part. Generally each coil is a specialized size and shape depending on customer requirements so there is very little repeatability involved in the production process of these products. This paper looks at the practicality of printing copper induction coils that could provide appropriate material properties, such as electrical conductivity. The paper also focuses on which printing method(s) might be the most efficient and/or practical. There has been little research done on the 3D printing of copper material compared to other metals such as steel, and the majority of research that has occurred focuses on material properties; mainly thermal conductivity. This study focuses on the practicality of the printing of the physical shapes, specifically a hollow curved or spiral shape. The most common and successful method that has been used thus far utilizing additive manufacturing (AM) for the production of copper parts is investment casting, where the mold is created using AM. While this method has merits, it isn’t a directly printed part. Also successfully casting a hollow curved or spiral shape would be extremely difficult and likely not practical. Induction coils can take on a seemingly unlimited amount of shapes and sizes. However, typically there tends to always be two main characteristics for a coil, those are: some type of hollow tubing is utilized for water cooling, and the existence of curved paths. These two characteristics in combination present some difficult hurdles regarding the physical printing of the part. Another major difficulty is the fact that the final material must be very dense in order to afford the superior electrical conductivity properties, which standard copper used for electrical purposes has. The main processes inspected for this study are powder bed fusion, namely selective laser melting, selective laser sintering, electron beam melting as well as direct energy deposition, using either powder or wire for the material feed. After considering all the various techniques for applying additive manufacturing to create induction coils, the selective laser melting process seemed to be the most practical and showed the most promise.

Recent Publications: John Martin

John Martin, an assistant professor of engineering technology at Youngstown State University, has recently presented for the American Society for Engineering Education and the American Society of Mechanical Engineers. Martin holds a bachelor’s and master’s degree in mechanical engineering and his research area is in engineering education.

Work in Progress: The Effects of Concurrent Presentation of Engineering Concepts and FEA Applications”, Martin, J., Martin, A., Proceedings of the 2016 ASEE Annual Conference and Expo, New Orleans, LA, June, 2016.

“CFD Analysis Comparing Steady Flow and Pulsatile Flow through the Aorta and its Main Branches”, Martin, J., Proceedings for the 2016 ASME International Mechanical Engineering Congress & Exposition, Phoenix, AZ, November, 2016.

Recent Publication: John Martin

John D. Martin, assistant professor of Mechanical Engineering Technology at YSU, co-authored a paper with Anna M. Martin for the 2016 ASEE North Central Section Conference in Mt. Pleasant, MI, March, 2016.

The paper, “Interleaved Practice for Engineering Concepts,” outlines the main points of a proposed study that aims to enhance the educational approaches used in engineering classrooms. Martin’s main area of research is in engineering education.

From the ASEE website:

Founded in 1893, the American Society for Engineering Education is a nonprofit organization of individuals and institutions committed to furthering education in engineering and engineering technology. It accomplishes this mission by

  • promoting excellence in instruction, research, public service, and practice;
  • exercising worldwide leadership;
  • fostering the technological education of society; and
  • providing quality products and services to members.

In pursuit of academic excellence, ASEE develops policies and programs that enhance professional opportunities for engineering faculty members, and promotes activities that support increased student enrollments in engineering and engineering technology colleges and universities. Strong communication and collaboration with national and international organizations further advances ASEE’s mission.

ASEE also fulfills its mission by providing a valuable communication link among corporations, government agencies, and educational institutions. ASEE’s 12,000+ members include deans, department heads, faculty members, students, and government and industry representatives who hail from all disciplines of engineering and engineering technology. ASEE’s organizational membership is composed of 400 engineering and engineering technology colleges and affiliates, more than 50 corporations, and numerous government agencies and professional associations. ASEE directs many of its efforts at providing for open and ongoing dialogues among these groups.

Faculty Faction: John Martin

John Martin, assiJohn Martinstant professor of Mechanical Engineering Technology, is a lifelong penguin. He earned his bachelor’s and master’s degrees in mechanical engineering at Youngstown State University.

He has worked in the industry for companies such as WCI Steel, Webco Industries, Ajax TOCCO Magnethermic, PMC Colinet, and RMS/Steelastic.

Martin said that if he ever got the chance to teach at YSU that he would, and that opportunity came to him last fall semester.

“It was something that I had in the back of my mind,” He said. “I came from industry, so that was kind of what I had always planned on doing, and if the opportunity ever arose that I could teach [at YSU], I wanted to; I just didn’t know if that was going to be a possibility.”

Martin said he hopes to be a big influence on his students so that one day they will look back and remember that he helped them to really understand the fundamentals of engineering and use it to their full potential.

Besides using his expertise to teach students about mechanical engineering technology, he has also been researching classroom instruction techniques.

“Right now, I’m doing research in engineering education,” Martin said. “I am currently evaluating different instructional methods in the classroom; for instance, the effectiveness of simultaneously presenting a software program while teaching a new mathematical concept versus sequentially presenting the software program and the concept.  My goal is to better understand how these methods effect learners in an engineering classroom to ultimately improve student learning.”

He also thinks that STEM is the perfect place to be if you want to be a part of the large diversity of both students and faculty on campus.

“I like the interaction with the students. I like meeting all the different people and personalities. There’s a lot more human contact teaching in STEM than there is in most industry jobs,” he said.