THE INNOVATIVE EDUCATOR
Personalized Learning
One of the learning outcomes for technical education is to ensure learners are prepared to be employed for the 21st-century workforce. Technical education’s instruction should include subject content material that provides the cognitive competencies and hands-on technical skills to solve authentic problems in society. As Loveland and Love (2017) have observed, technology continues to evolve at a rapid pace. Further, Loveland and Love (2017) explained as this rapid pace in new products continues technological literacy is required to design and maintain these innovative devices and systems. To provide an assistive method in teaching technological literacy in a classroom environment, an appropriate learning theory needs to be selected. According to Pourhosein Gilakjani et al. (2013), a learning theory helps to support or ground the instructional method used in a classroom environment. With such a learning theory selected, the instructional infrastructure can establish the direction to guide the educator in instructing or facilitating the learning environment. Therefore, the two learning theories that may be deployed in an Industrial Maintenance Technology learning environment are constructionism and constructivism. Industrial Maintenance Technology.
Rob and Rob (2018) explained constructivism as an educational philosophy created by Jean Piaget. With this educational philosophy, learners are active actors in constructing their own learning through personal artifacts. Further, Rob and Rob (2018) noted effective learning occurs when the learner is engaged with the construction development of their selected personal artifact. This educational philosophy contrast with constructionism whereby the learning theory allows learners to collaborate in constructing a real-world product. Constructionism was created by Seymour Papert of the MIT Media Lab. Papert’s constructionism theory was inspired by Piaget’s constructivism approach to the learning development and growth of children. The key aspect of both learning theories is metaphorically based on constructing knowledge either through personal artifacts or real-world products.
The association of constructionism and constructivism to personalized learning is the educational artifact or product created by a learner or the collaborative group. Also, learning experiences will be enhanced using both constructionism and constructivism theories. In comparing these learning aspects with Childress and Benson’s (2014) description of personalized learning as the “student learning experiences” both learning theories align with the personalized instructional strategy. Further, the hands-on learning outcome of developing 21st-century cognitive competencies and psychomotor technological skills positively correlates with Industrial Maintenance Technology’s technical curriculum and classroom environment. Therefore, learning how to read advanced motor drive electrical-electronic system block diagrams, computer coding ladder logic programs for Programmable Logic Controllers (PLCs), and building new control interfaces with littleBits electronic modules align with learner-centered education and development of constructivism and constructionism learning theories. The personalized learning-based industrial system trainers and digital programmable manipulative used in the Industrial Maintenance Technology curriculum appear in Figure 1. The instructional vision is with these two learning theories learners will take responsibility for their continuum of technical education.
Research on using technology to support personalized learning
To enable the constructivism and constructionism learning theories that support personalized learning, technology integration plays a critical role. There are a variety of philosophies, strategies, and best practices discussed in the literature when integrating technology into the learning environment. One broad spectrum perspective associated with technology integration is Kopcha’s (2010) system-based model. Kopcha (2010) noted Technology Integration plays an important role in the creation of digital learning communities. With such technology integration, K-12 and post-secondary education is being transformed to provide digital literacy through shared knowledge to learners. This shared digital literacy knowledge method correlates with Vygotsky’s Social Constructivist approach to learning. Solovieva and Quintanar (2016) explained Vygotsky’s Social Constructivist theory directs social learning based on learners' individual experiences with technology. Further, Solovieva and Quintanar (2016) noted the shared individual experiences with technology such as educational robotics aligns with Vygotsky’s work on Zone of Proximal Development (ZPD). Solovieva & Quintanar (2016) explained, as relating to social learning, ZPD is the actual developmental stage where a learner can understand a new task with assistance from an educator or learner. The personalization with educational robotics technology lies in coding the small autonomous machine based on the learner’s own constructed vision and interest in motion, light, and sound of their personal creation. Figure 2 illustrates one variety of educational robots that can be used for personalized learning.
This instructional method of using educational robotics as a personalized learning technology connects with Pourhosein Gilakjani et al. (2013) constructivist approach to engaging the learner with the delivered subject content material through encouragement, acceptancy, initiative, and self -directiveness. Another benefit to integrating educational robotics with personalized learning is based on authentic learning through creativity and problem-solving. As explained by Alimisis et al.'s (2007) seminal work on robotics education, meaningful learning through the creative construction of educational robots can be achieved by the learner. Moreover, Alimisis et al. (2007) noted authentic learning obtained from engaging with educational robots enhances the problem-solving experiences of the learner. These learning objectives can only be achieved by creating a learner-centered environment using such personalized learning technology as suggested by Alimisis et al. (2007) educational robotics work.
In addition to educational robots, Learning Management Systems (LMSs) provides innovative methods for learners to embrace their own learning through personalization. The personalized learning article written by Francis (2017) explored some innovative techniques in using this instructional method in the learning environment. The overall conceptual approach that Francis (2017) discussed in his secondary literature perspective article was the use of a Learning Management System (LMS) to facilitate personalized instruction for a group or classroom of learners. As Francis (2017) noted, one challenge confronted by educators in implementing PL is time. Devising individual Personalized Learning Plans (PLPs) is a time commitment placed on the educator in assessing their learners. Therefore, time becomes a barrier met with reluctance by the educator. Ripp (2015) argued the challenge of personalized learning is it becomes overwhelming due to the amount of time required in creating the plan.
The concept that Francis (2017) proposed in his article was the use of software designed to direct learners through lesson topics they can work on at their own pace. As explained by Francis (2017), an LMS’s hardware and software components will make It possible for the educator to provide a high degree of personalization without the load-bearing condition of additional work. Another personalized learning concept that Francis (2017) discussed was leveraging mobile personal devices within the instructional framework. Further, Francis (2017) noted that mobile personal devices like smartphones and tablets play an important role in personalized learning. The importance as Francis (2017) described relies on the learner’s uninterrupted access to the specific course instructional content material. Moreover, Francis (2017) suggested educational apps can be installed on these mobile personal devices, thereby allowing the educator to facilitate learning with their learner. In addition, Francis (2017) explained with the educational app the learner will have access to the LMS anywhere and at any time (Bramante & Colby, 2012).
A Personalized Learning Approach
Two personalized learning approaches that can be explored in an Industrial Controls I course are Project-Based Learning and Genius Hour. The learner efficacy achieved with project-based learning is authentic education and training. Hickey (2014) noted project-based learning can be used in all instructional courses to allow real-world knowledge and skills to be obtained by the learner. Another personal benefit to project-based learning as explained by Hickey (2014) is learners can arrive at the answers from a variety of learning approaches. Further, Hickey (2014) stated learners can develop multiple solutions for a specified project.
Therefore, wiring electrical motor controls on an industrial system trainer will be presented in a variety of build schemes by technical learners. In addition, the Disciplinary Outcome achieved from this personalized learning approach is based on competencies aligned with educational or industrial standards. Moreover, the competencies from the electrical motor control wiring activity that aligns with this Disciplinary Outcome are: interpret specified motor control circuits and apply control concepts in circuit construction.
Personalized Learning Activity: A Bluetooth SNAP Transistor Inverter Circuit
The following personalized learning Activity that aligns with constructionism theory is an Internet of Things Bluetooth SNAP Transistor Inverter circuit activity. The technical instructor can facilitate a technology learning activity that demonstrates wireless control techniques assisted by electronics and visual programming technical instruction. The Bluetooth SNAP Transistor Inverter uses an M5 Core2 unit, 32bit ESP32 microcontroller embedded with a short-range Bluetooth transceiver chipset. The chipset follows the Bluetooth Sig 5.0 industry standard, thereby allowing technical learners to explore the advanced short-range wireless Information and Communication Technology (ICT) specification in a class or electronics laboratory environment. The transistor inverter is a digital circuit used in a variety of industrial controls machines and applications. With this personalized learning activity, technical learners will understand the operation of an NPN transistor operating as an electronic switch. The use of SNAP circuits will remove the challenge of learning electronics by the parts integrated within colorful plastic shapes. The electronic symbols for the hands-on project are stamped on the plastic shapes. Figure 3 shows the electrical wiring diagram for the Bluetooth wireless controller project-based learning activity.
The equivalent electronic circuit schematic diagram for the project-based learning activity is shown next.
The final prototype build of the project-based learning activity is provided next.
The visual blockly code is used to configure the user interface and Bluetooth function of the M5 Core2 Controller.
The operation of the M5 Core2 Bluetooth — SNAP transistor inverter circuit consists of the following events.
· The M5 Core 2 controller will display the ON and OFF operational state of the NPN Q2 Transistor.
· The LEDs D1 and D2 will provide the operational status of the NPN Q2 transistor.
· D1 LED will turn ON when the NPN Q2 transistor is switched ON.
· D2 LED will ON when the NPN Q2 transistor is switched OFF.
The operation of the M5 Core 2 Bluetooth-SNAP transistor inverter circuit can be viewed on YouTube by clicking on the link below.
With a mobile device like a smartphone or tablet and the appropriate Bluetooth app installed on the device, the M5 Core2 controller will wirelessly switch the transistor inverter circuit ON or OFF. A wireless Bluetooth control and monitor app that works well with the M5 core is Nordic Semiconductors’ nRF Connect or Toolkit. The wireless electronics project allows technical learner agency through the following circuit and visual coding activities.
a) Experimenting with R1 and R2 resistor values and observing the circuit operation.
b) Changing the User Interface appearance through visual coding to represent the digital operation of the inverter circuit.
c) Measuring the total circuit current and the base-emitter voltage with a digital multimeter.
d) Replace the existing LEDs with different color emitting parts.
e) Changing the interaction mode where the technical learner selects ON and OFF controls by using the M5 Core2 controller touchscreen.
f) Wire the SNAP transistor inverter circuit using discrete electronic parts on a standard solderless breadboard.
The overall goal of Personalized Learning is to provide a wealth of technology resources to support the journey of self-directed and lifelong knowledge engagement for the technical learner. It is with this self-directed learning environment, ownership in one’s education and training can be instilled within each technical learner. The personalized learning project and suggested activities will allow learner agency to permeate within a technical learning environment.
References
Alimisis, D., Moro, M., Arlegui, J., & Pina, a. (2007). Robotics & constructivism in education: The TERECoP project. EuroLogo, 1–11. http://users.sch.gr/adamopou/docs/syn_eurologo2007_alimisis.pdf
Bramante, F. J., & Colby, R. L. (2012). Off the clock: Moving education from time to competency. Thousands Oak, CA: Corwin.
Childress, S., & Benson, S. (2014). Personalized learning for every student every day. Phi Delta Kappan, 95(8), 33–38. https://doi.org/10.1177/003172171409500808
Eyal, L. (2012). Digital assessment literacy — The core role of the teacher in a digital environment. Educational Technology and Society, 15(2), 37–49.
Francis, S. (2017). The power of technology in facilitating personalised learning. International School; Woodbridge, 19(3), 23–25.
Hickey, B. R. (2014). Project-based learning: Where to start ? Techniques: Connecting Education & Careers, 80(2), 8–9.
Kopcha, T. J. (2010). A systems-based approach to technology integration using mentoring and communities of practice. Educational Technology Research and Development, 58(2), 175–190. https://doi.org/10.1007/s11423-008-9095-4
Loveland, T., & Love, T. (2017). Technological literacy: The proper focus to educate all students. Technology and Engineering Teacher, 76(4), 13–17.
Pourhosein Gilakjani, A., Mei Leong, L., & Nizam Ismail, H. (2013). Teachers’ use of technology and constructivism. International Journal of Modern Education and Computer Science, 5(4), 49–63.doi:.10.5815/ijmecs.2013.04.07
Ripp, P. (2015). 9 barriers to personalized learning and how we may work around them. 1–6. https://pernillesripp.com/2015/01/16/9-barriers-to-personalized-learning-and-how-we-may-work-around-them/
Rob, M., & Rob, F. (2018). Dilemma between constructivism and constructionism: Leading to the development of a teaching-learning framework for student engagement and learning. Journal of International Education in Business, 11(2), 273–290. doi:.10.1108/JIEB-01–2018–0002
Solovieva, Y., & Quintanar, L. (2016). The zone of proximal development during assessment of intellectual development in pre-school children. Psychology in Russia: State of the Art, 9(4), 123–137.doi:.10.11621/pir.2016.0410
Zumda, A., Curtis, G., & Ullman, D. (2015). Learning personalized: The evolution of the contemporary classroom. Jossey-Bass.
