Seven factors play an important role in the learning process, also known as (a.k.a.) "the 7 E's".  First, the right kind of Environment must be set up in order for students to learn new materials well.  Whether it's a lecture theatre, classroom, laboratory or even a student's study desk at home, the Environment must be set up with everything needed to present the materials, tools and/or components needed for students to experience all the other 6 stages of learning.  An ideal learning environment at home is free from all sources of distractions, such as noise from other people and frequent interruptions from mobile phones, social media websites and computer notifications, so that a student can focus, concentrate, and avoid multi-tasking.  (Why?  Because the human brain can only focus well on processing one thought or one idea at a time.)  For project work at University, where students work in teams to develop a project, each team needs access to the internet and all class materials should be easily accessible online, such as on the course's web page (organized by each week), in order to make access to information quick and easy.

Learning new information becomes much easier if a student has genuine Enthusiasm for a particular topic.  Such a positive feeling may not be initially present nor at a high level for every student, therefore, the instructor needs to develop or stimulate curiosity and 'interest', so that every student can appreciate why the topic is important to learn and master.  It is not enough to just explain the 'what' (or only the content), but also the 'why', so that students can feel a sense of 'buy in'.  For example, think of the way most customers do not like to feel pressured into buying something they believe they do not need.  According to the book: "The Laws of Human Nature", most people view themselves as 'Free [or independent], Intelligent and Good' ...  Most people value their 'free will' and do not want to feel forced into learning or doing something they do not regard as useful.  Many students want to feel like a given topic is really useful to them (or their future career), before they put in all the hard work in learning it.  Some students - especially most of the high-school or University dropouts who become founders and CEOs of successful startup companies -  are very independent thinkers and don't like feeling coerced or pressured into doing something they don't believe is important.  (Refer to the book: "Why A students work for C students, and B students work for the Government")...  

Some independent minded students want to feel like they are 'in control' of what they are learning, and that they still get to 'choose' whether to learn something or not.  By explaining why a particular topic is important to learn, and where it fits into the 'Big Picture' (of their professional skills), there will be much less resistance to learning that new topic.  Many students want to know how each topic will be beneficial and advantageous to them in the future.  In other words, students want to appreciate the value or importance of everything they are learning - similar to how a customer needs to know the key benefits of a new type of product, before buying it.  As the teacher, it is important to highlight the benefits and purpose of each and every topic you are teaching, before teaching it and going into great detail, in order to develop enough enthusiasm and motivation for learning.  In order for material to be useful, students need to know how to use it, and where and when to use it.  This can be demonstrated by working through suitable detailed example problems.  If you can develop a high level of enthusiasm, students can become excited, self-motivated, and eager to learn and research many things on their own.  The positive feelings of enthusiasm, excitement, curiosity and optimism are essential driving forces for 'Lifelong learning' and the long hours of research and work that are necessary to design, develop and complete large and complex projects.  These kinds of emotions should be encouraged, because they serve as the 'fuel' for self-motivation.

Each person has a proclivity to learn better from a particular form of sensory input, such as visual (seeing text, graphs, pictures, videos), auditory (hearing verbal speeches, sound recordings, music, etc.), kinesthetic (hands-on manipulation, physical movement, copying a sequence of actions, etc.), and even touch, smell or taste senses (especially for cooking classes).  The more of these kinds of sensory inputs are used to teach a particular topic, the better the information will be remembered and the more students will be engaged, because each kind of sensory input creates a different type of memory in the brain.  A very large percentage of students, in fact, prefer 'hands-on' learning.  Students do not really feel like they have mastered a particular skill until they have performed it themselves with their own hands, without direct instructions or guidance from a supervisor or instructor.

Exposure of the learning materials can be done in many different ways, however, I prefer to keep my lecture and lab presentations as simple as possible, using visual pictures and often multimedia (video) presentations,  so that all students at all levels can understand everything clearly...  If more than 10% of the  students fail to understand what I am teaching, then I have failed as a teacher, because I do not want more than 10% of any class to fail the course...  I start with showing (visually) and describing (verbally) very simple ideas and basic concepts, with (hands-on) examples of how such concepts are used, and over time, I increase the complexity of my examples.  To make the material clear, easy to learn and absorb, I slowly build on the existing knowledge of students.

According to Tony Robbins (from the self-help book: "Unleash the power within"), good teaching is all about connecting or relating what is new or unknown to what students already know... This is known as 'scaffolding', or building up on existing knowledge, and is an effective way to minimize confusion and learning pain.  For example, when trying to explain how a resistor works, most students who are new to electronics have no experience with electric current, because it is invisible.  However, most students know how water flowrate can be adjusted with a tap (with a twist-top handle).  You can tell students that electric current is like the flow of water coming out of a tap.  The tap adjusts the size of a hole for the water to flow through.  The smaller the hole size, the greater the resistance to flow, therefore, the water flowrate will be lower.  The larger the hole size, the lower the resistance to flow, therefore, the water flowrate will be higher.  Likewise, if you choose a high value for a resistor, the electric current will be low.  If you choose a low value for a resistor in a current path, the electric current will be high.  (Ohm's Law says: Current = Voltage / Resistance,  or  I = V / R ... i.e. Electric current is inversely proportional to the Resistor value in a circuit ).

Many students experience confusion and frustration when a teacher tries to explain a totally new concept that has no connection to concepts that the students are already familiar with.  For example, you may ask a class of first-year engineering students: "Why does a submerged beachball, when released from underwater, always float upwards?"... or "Why does oil, when released underwater, always float upwards to the top of the sea?"... (You can even demonstrate this with a live experiment, using a fish tank full of water, and releasing a blob of oil trapped under a glass or cup, starting from the bottom of the fish tank)...  It is difficult to explain why a lower density fluid (like oil) when submerged under a higher density fluid (like water) must rise upwards to the top of the water surface... by saying this is similar to how a helium balloon always floats upwards in open air... The reasons for the upward floatation phenomenon are indeed similar, but both concepts would probably still be unfamiliar to most students.

However, most students can be convinced of the principle:  Force = Pressure x Area, or F = P x A.  This is a familiar concept taught in High-school-level physics and science classes.  As the teacher, you can ask the class: "Have you ever noticed, when you are swimming, that the deeper you go under water, the more pressure you experience on your ears?" ... Most will agree.  Then say: "That's because of the weight of the water above your head.  You experience more pressure, as you go deeper underwater.  The pressure you experience is proportional to how deep you go below sea level, or the distance between the sea level and your position."  Most students would agree with this.  Now say: "Imagine a big blob of oil, the size and shape of a spherical basketball, is released underwater, from some leaky pipe.  Why does it float upwards?"... then get the students to think and given them a chance to come up with a logical explanation.   Most students who do not have access to ChatGPT will have difficulty putting together all those clues mentioned before... But give the entire class this question to see who can come up with a good explanation...  The correct answer is: "The pressure acting on the top half of the oil blob is slightly lower than the pressure acting on the lower half of the oil blob... because the top half is closer to the sea level, due to slightly less water depth above the top half of the spherical blob.   Therefore, the force on the bottom half of the blob is greater than the force acting on the top half of the blob.  This force difference causes a net upward force that drives the blob up towards the sea level... and the same is true for a helium balloon floating upwards in air.  The pressure of the air acting on the top half of the balloon is slightly less than the pressure acting on the bottom half of the balloon."   Notice how this makes logical sense to students when you start by explaining new concepts with things they already know... (1) Pressure increases based on the weight or distance of fluid above an object... (2) Pressure = Force divided by Area, or Force = Pressure x Area...

After going through the material for each topic, I ask students review questions and give them problems to solve with the correct answers or results, so they can check their understanding.  I also ask questions in class (without focusing on any particular student), to gauge their understanding and level of engagement.  Student knowledge is usually tested with online (Moodle) quizzes or exams.  Their theoretical understanding can be assessed regularly using written reports or assignments.  Their practical skills can be evaluated by asking them to complete lab activities and demonstrate the results (e.g. show working experiments, output for software code, etc.).  However, I do not ask students to perform a task that requires knowledge or skills that I have never demonstrated before in class (except for small research assignments).  Every type of skill that I expect students to learn and master must be demonstrated by me first, in class.  This is very important.  When students who have attended all my classes repeatedly keep failing to perform an assignment or lab task successfully, despite all their efforts, this puts them at risk of feeling like a failure, losing confidence and wanting to give up or quit the course.  Such students could lose their enthusiasm, feel very frustrated, and develop real hatred and contempt for me and the course.  Students who experience many failures, despite all their hard work, will (rightfully) start to believe that the teacher had set a task that is far too difficult, too complex, or impossible to complete.  This indicates that students were not adequately prepared for completing such a task.  Perhaps they were not given enough information or were not taught the required kinds of skills needed to complete the task.  Maybe there were not enough worked examples that they could imitate or study, to solve the problem.  As the teacher, it is important to avoid making such mistakes, to keep students feeling positive.

Give students Easy exercises to complete successfully, to build up their confidence in each area.  For example, when teaching students how to solve a problem, use complicated software, or how to program code, it is best to demonstrate such skills using several short demonstrations, each being about 5 minutes long (on  average).  Psychology studies have discovered that most people can only remember an average of 7 things (plus or minus two) in their short-term memory.  This means most students can only remember about 5 to 9 things at a time.  Almost everyone can remember at least 5 things in their head at any given moment in time, therefore, I choose to avoid teaching students more than 5 new things in any 5 minute demonstration, so that all students can follow along easily.  I choose a short demonstration period of 5 to 7 minutes at a time, so that students can still remember almost everything they have seen very easily.

For example, when I teach students how to use AutoCAD or SolidWorks software to create CAD (Computer Aided Design) drawings on a computer, I usually spend about 5 minutes at a time  demonstrating how to perform essential skills.  e.g. This is an example of a 5 minute demonstration:  

(1) Briefly explain each part of the software screen; 

(2) Show how to use the mouse to change the view - Zooming in and out, Panning, Rotating the camera view; 

(3) Select the starting layer to begin sketching; 

(4) Create a simple circle 2D sketch; and 

(5) Use the "Extrude" command to create a 3D cylinder solid.  

Students watch me doing this 5 minute live demonstration (with my entire computer desktop shown on the projector screen).  I encourage students to ask questions if they feel lost or confused.  After the 5 minute demonstration, I ask the students to copy what I just showed them, on their computer.  They also have access to a "Step by step" guide (web page or PDF document), containing simple instructions for all the steps I just showed them.  All information, lecture notes, lab activities and notes are accessible online, in chronological order - grouped by 'Teaching Week' number, or date, so all relevant information can be found and accessed quickly and easily, in one place.  (e.g. use a Learning Management System or LMS, like Moodle or Blackboard). 

Between each of these 5 to 7 minute demonstrations, I usually walk around the room for about 10 to 15 minutes to check how students are doing.  Once they have successfully performed those tasks "hands on", they have mastered those skills.  In the next 5 minute demonstration, I go on to make a more complex shape, like a 'Gingerbread man biscuit' model which requires students to draw a more complicated 2D sketch to be extruded.  Such a lab session can run for about 2 - 3 hours, without any students feeling bored or frustrated, because they feel like they are really learning and applying new skills.  I teach my Mechatronics and software labs in a similar manner.  I perform a short demonstration for about 5-7 minutes, and give about 10-20 minutes for students to copy what I have done, and so on.  A few homework exercises are set for the students to complete, where they must use similar kinds of skills, and those homework exercises are graded in the following week in the labs, so that instant feedback is given to each student, in person, about any mistakes they have made.  It is very important that you praise students on a 'job well done' to keep them positive and feeling successful.  Too much focus on criticism and negativity can destroy a person's self-confidence and motivation.  Criticism should be avoided as much as possible... It should be given only for violations of moral principles, and only discussed in private to avoid embarrassing or offending a student.  It is very important to keep all learning activities simple to complete, so that students will feel successful, and will continue feeling positive and excited about their progress.

Once students  have mastered enough basic skills, they will be able to complete a large project that requires the use of all those skills demonstrated.  For example, if it is CAD assignment, you can ask them to produce a 3D model of a complex mechanical component, like a ball bearing housing.  If it is a mechatronic lab, students can be asked to build and program the microcontroller and 2 H-bridge circuits to remote-control a small mobile robot driven by 2 DC motors that drive skid-steering wheels, with variable speed control.  As the instructor, the most you need to show students is how to program the microcontroller software and set up the H-bridge circuit to control the direction and speed of one DC motor, and let them Experiment and figure out the rest.  Think of everything you are showing them as being like small 'building blocks' of a larger system that they must design, build and test.  Let the students figure out how to write their own steering control and speed control software algorithms (and offer small hints if they get stuck), and how to build their own dual H-bridge circuits, driven by the PWM (Pulse Width Modulation) timer pins of the microcontroller chip.  There are usually two or more ways to get something done, so leave this for the students to decide.  Give students the opportunity to figure out answers and solutions for themselves, so they can develop their own creativity and imagination.  Students can develop high levels self-confidence when they can see their own original ideas and designs working in the real world, without being told every detail about everything they need to do.  Think about how much fun it was when you were a little child, building all kinds of structures using 'LEGO' building blocks.  Creating different kinds of shapes was fun because you had total freedom to make your own decisions, you could immediately see the results of your work, and you were not being forced to do something by your parents.  Likewise, in a mechatronics lab, students can quickly see the results of their decisions and choices, and their experiment either works, or it doesn't.  If it doesn't work, they are responsible for finding and fixing any mistakes they had made.  They can also learn from their mistakes and failures, and develop better problem solving skills.

Most students find project work to be very exciting, challenging and enjoyable, because it requires them to make their own decisions, think creatively and use their imaginations (because there are no 'complete' solutions to a large project provided by the instructor).  Creative thinking and decision-making design skills are not often developed in most Engineering courses, however, creativity is encouraged in courses for music, visual arts, dancing and languages - especially for fiction writing and storytelling.  Many students enjoy this form of creative Expression, because they have total freedom to design their machine or robot and make their own design decisions.  For example, in one year, students were asked to design and build a remote-controlled vehicle to collect boxes on a playing field that was covered with many big obstacles.  Each team (of two students) also had to design their own mechanism or device for holding or storing the boxes, so they could be transported back to the home base.  This resulted in many different kinds of designs being built, because there were many ways to hold onto such boxes.  The winning team was the one that returned the most boxes to their 'home base' within the 3 minute time limit.  See the video of the 'Box Collecting' competition below.

Most students are also keen to compete with other students in competitions, such as sensor-guided racing car competitions, Micro-mouse maze solving contests and even 'Robot Wars'.  You can read more about how these competitions are organized in this paper.  Such events turned out to be a lot of fun, and often attract much media attention.  For example, a 'Robot Wars' competition that I organized in Perth was featured on Channel 10 TV news, and in a local newspaper.  The students who enjoyed these kinds of projects usually go on to develop amazing and very complex 'Final year' (capstone) projects in their 4th year of engineering, using their skills to build complex controllers and instrumentation for monitoring engines and vehicle status (to measure things like vehicle speed, gear status, fuel level, etc.).  Such students develop very high self-confidence in their abilities, and a passion for technical innovation and inventing.  Actually, a few of my students who completed such project-based courses that I taught started their own successful engineering and technology businesses that provided jobs for many graduate Mechatronic engineers.

At the end of the semester, each team of students is asked to present a short talk in front of the class explaining their major project work.  They stand in front of their peers and practice their presentation and communication skills using software such as 'PowerPoint' or 'Presi', and some even play short demonstration videos.  Students present their work, what they designed and the results they achieved.  They must also answer questions from the audience or the instructor.  A written report, documenting all their design work (e.g. photos, descriptions, electronic circuit schematics, software code, CAD drawings, references to information, etc.) is also prepared and submitted for grading.

I was told once by Professor John Billingsley (paraphrased): 'The best way to master any subject, is to teach it' ... because students will ask you all kinds of questions, so you will need to know everything about that subject or topic.  I would also add: 'The best way to remember and recall knowledge and concepts is to Educate others, and keep reviewing that information over and over' - verbally, or in written form (published in a book or as course materials).  By teaching others what you know, you are helping to refine and improve your own skills (through deep research), while refreshing your own memory.  Also, ‘The best way to remember practical skills, like software programming or electronic circuit design, is to build and test your own original projects without copying any existing code, or without using someone else’s circuit design’… (DIY – Do It Yourself) 

Robotics is the applied science of motion control for multi-axis manipulators and mobile robots (or 'ROV' - Remote Operated Vehicles) and is a large subset of the field of "mechatronics" (Mechanical, Electronic and Software engineering for product or systems development, particularly for motion control applications). Mechatronics is a more general term that includes robotics, positioning systems, sensors and machines that are controlled by electronics and/or software, such as automated machinery, mobile robots and even your computer controlled washing machine and DVD movie player.  Most of the information taught in mechatronic engineering courses around the world stems from industrial robotics research, since most of the earliest actuator and sensor technologies were first developed and designed for indoor factory applications.  A 'Mechatronic Engineer' has the detailed practical knowledge and skills needed to design and build most kinds of computer-controlled or electronic-circuit controlled hardware, such as industrial automation equipment, machines and devices.  Universities that offer a 'Mechatronic Engineering' degree usually require their students to study subjects in the fields of Mechanical engineering, Electrical & Electronics engineering, and Software engineering (usually over a 4 year time period).

Robotics, sensors, actuators and controller technologies continue to improve and evolve at an amazing rate. Automation systems and robots today are performing motion control and realtime decision making tasks that were considered impossible just 40 years ago. It can truly be said that we are now living in a time where almost any form of physical work that a human being can do can be replicated or performed faster, more accurately, cheaper and more consistently using computer controlled robots and mechanisms. Many highly skilled jobs are now completely automated. Manufacturing jobs such as metal milling, lathe turning, pattern making and welding are now being performed more easily, cheaper and faster using CNC machines and industrial robots controlled by easy-to-use 3D CAD/CAM software. Designs for mechanical components can be quickly created on a computer screen and converted to real-world solid material prototypes in under one hour, thus saving a great deal of time and costly material that would normally be wasted due to human error.  Industrial robots and machines are being used to assemble, manufacture or paint most of the products we take for granted and use on a daily basis, such as computer motherboards and peripheral hardware, automobiles, household appliances and all kinds of useful whitegoods found in a modern home. In the 20th century, engineers have mastered almost all forms of motion control and have proven that robots and machines can perform almost any job that is considered too heavy, too tiring, too boring or too dangerous and harmful for human beings.  Human decision making tasks are now being automated using advanced sensor technologies such as machine vision, 3D scanning and a large variety of non-contact proximity sensors.  The areas of technology relating to sensors and control are still at a fairly primitive stage of development and a great deal of work is required to get sensors to perform as well as human sensors (vision, hearing, touch / tactile, pressure and temperature) and make quick visual and auditory recognitions and decisions like the human brain. Almost all machine controllers are very limited in their capabilities and still need to be programmed or taught what to do using an esoteric programming language or a limited set of commands that are only understood by highly trained and experienced technicians or engineers with years of experience. Most machines and robots today are still relatively "dumb" copiers of human intelligence, unable to learn and think for themselves due to the procedural nature of most software control code.

In essence, almost all robots today require a great deal of human guidance in the form of software code that is played back over and over again. The majority of machine vision and object recognition applications today apply some form of mechanistic or deterministic property-matching, edge detection or colour scanning approach for identifying and distinguishing different objects in a field of view. In reality, machine vision systems today can mimic human vision, perception and identification to a rather crude degree of complexity depending on the human instructions provided in the software code, however, almost all vision systems today are slow and are quite poor at identification, recognition, learning and adapting to bad images and errors, compared to the human brain.  Also, most vision systems require objects to have a colour that provides a strong contrast with a background colour, in order to detect edges reliably.  In summary, today's procedural-software-driven computer controllers are limited by the amount of programming and decision-making "intelligence" passed onto it by a human programmer or engineer, usually in the form of a single-threaded application or a complex list of step-by-step instructions executed in a continuous loop or triggered by sensor or communication "interrupts". This method of control is suitable for most repetitive applications, however, new types of computer architecture based on how the human brain works and operates is unchartered research area that needs exploration, modelling and experimentation in order to speed up shape or object recognition times and try to minimize the large amount of human effort currently required to program, set up and commission "intelligent" machines that are capable of learning new tasks and responding to errors or emergencies as competently as a human worker.

The biggest challenge for the 21st century is to make robots and machines "intelligent" enough to learn how to perform tasks automatically and adapt to unforeseen operating conditions or errors in a robust and predictable manner, without the need for human guidance, instructions or programming. In other words: "Create robot controllers that are fast learners, able to learn and perform new tasks as easily and competently as a human being just by showing it how to do something only once.  It should also learn from its own experiences, just like a young child learning and trying new skills."  Note that a new-born baby knows practically nothing but is able to learn so many new things automatically, such as sounds, language, objects and names.  This is a "tall order" and sounds very much like what you would expect to see in a "Star Wars" or "Star Trek" science fiction film, but who would have thought, in the middle of the 20th century, that most people could be instantly contacted from almost anywhere with portable mobile phones, or that you could send photos and letters to friends and family members instantly to almost anywhere in the world, or that programmable computers would be smaller than your fingernails?  Who ever thought that a robot can automatically perform Cochlear surgery and detect miniscule force and torque changes as a robotic drill makes contact with a thin soft tissue membrane which must not be penetrated? (A task that even the best human surgeons cannot achieve consistently with manual drilling tools) Who would have imagined that robots would be assembling and creating most of the products we use every day, 40 years ago?  At the current accelerating rate of knowledge growth in the areas of robotics and mechatronics, it is not unreasonable to believe "the best is yet to come" and that robotics technology will keep on improving to the point where almost all physical jobs will be completely automated while hardware costs keep on dropping.  Mobile or "field" robotics is also a rapidly growing field of research, as more applications for robotic and mechatronic engineering technology are found outside the well-structured and carefully controlled environments of indoor factories and production lines.

Technological development is now at the stage where robots can be programmed to automatically plant and harvest food at low cost to end world hunger, engage in cooperative construction work to erect buildings and low-cost modular homes to house the poor, perform remote surveying and video surveillance (land, sea, air & on other planets), automatically build space stations or bases on the Moon or on Mars, perform fully automated mining operations deep underground, safely transport people in flying aerial vehicles to avoid slow road traffic, mow your lawn and recharge itself, guide blind people to their destinations using GPS or machine vision and save humans from the stress and boredom of highly repetitive production work in factories.  In fact, there is no limit to where practical robotic technologies may be used to improve how people work and live.  Rather than destroying factory and production jobs, robots are providing more opportunities for people to upgrade their skills to become technicians or robot operators who are spared the difficulties of strenuous, repetitive, potentially dangerous or very tiring or tedious manual labour.  We are not yet at the level of robotic automation depicted in films like "iRobot", "The Terminator" (movie series) or cartoons like "The Jetsons", where humanoid robots roam the streets freely, however, modern society appears to be headed in that direction and robots of all types could play an increasingly important role in our daily lives, perhaps improving the way we work, shop and play.

The one truth that faces us all is that life is short and it is important to do as much "good" as possible in the limited time that we are alive. It is important to leave behind a better world for future generations to inherit and enjoy so that they do not suffer unnecessary burdens, physical hardships, expensive education, poor employment opportunities or very high costs of living that leave them with little or no savings or financial incentives to work.  Robotic and mechatronic engineers, researchers and educators are in an excellent position to help leaders in education, business and politics to understand and realize the benefits of promoting robotic applications.  All it takes is the desire to do good for others and the kind of burning enthusiasm and zeal that makes it difficult to sleep at night!  Unfortunately, most Universities do not teach engineers how to be effective at developing, selling, promoting and commercializing new technologies, good ideas and useful inventions that could change the world.  Many education systems today still value "rote learning" and memorization skills over "Problem Based Learning" projects or design-and-build activities that promote creativity.  It is this kind of "inventor's mindset" and "entrepreneurial spirit" which motivated the great inventors and scientists of the past to keep tinkering, exploring and experimenting with new ideas and concepts which showed good potential for being useful and practical in the real world. In the "spirit of discovery", robotic and mechatronic engineers and researchers around the world are working hard, relentlessly pursuing their research goals in order to discover, develop and test a new great idea or a new technological breakthrough that could make a significant impact or improvement to the world of robotics and mechatronics.  Sometimes this work is arduous and difficult, requiring a great deal of patience and perseverance, especially when dealing with many failures.  In fact, good results cannot always be guaranteed in new "cutting edge" research work.

Despite much frustration, the veteran researcher becomes adept at learning from past mistakes, viewing each failure as a necessary, vital "learning experience" and an opportunity to make progress towards different goals which may present more interesting questions.  This kind of research and investigative work brings great joy when things are going well as planned. I have laughed many times when very conservative research engineers jump and even yell with joy when their experiments finally work for the first time after many failures.  The truth is, robotics and mechatronic engineering is very addictive and enjoyable because continuous learning and solving challenging problems with a variety of intelligent people makes every day different, unpredictable and fun.  Is technological change happening too fast?  Advances in tools and devices are now happening at such a rapid pace that often, by the time students learn a particular type of software or piece of hardware, it is probably already obsolete and something new and better has replaced it already.  For example, standard website development software tools keep changing every few years.  Another example... A very popular microcontroller chip family may require many months to master its hardware and assembly language, but it might end up discontinued (obsolete or no longer in production) by the time the student graduates... Another example... For decades, most computers and microcontrollers have been based on binary switching, and are pure digital devices... However, new analog computers and microcontrollers (and hybrid versions that are analog and digital) have recently been developed, which are functionally equivalent to digital computers, but are faster and more energy efficient... These new kinds of analog computer technologies require totally new training courses and programming methods for the next generation of engineers to use them.  It is almost impossible to "future-proof" any kind of system or product, simply because newer and better technologies and solutions are being developed every day.

Today, it is now virtually impossible for an engineer to be an expert in all areas of robotics and mechatronics engineering, however, it is possible to grasp the fundamentals and become an effective system integrator, able to bring together many different forms of technology to solve problems.  Mechatronic and robotic automation engineers are becoming increasingly dependent on using "off the shelf" devices, components and controllers.  Using such commercially available components saves a great deal of development time and cost, allowing system developers to focus on accomplishing the tasks of designing, building and testing complete automation systems or manipulators customized for specific applications.  Perhaps the most important learning skill for a mechatronic or robotics engineer is the ability to ask the right questions which could lead to the right answers.  A good 'Mechatronics Engineer' understands the "big picture" and knows how large systems of mechanical devices, electrical devices, controllers, sensors, software systems and data communication systems can work together to perform desirable functions.  The 'Mechatronics Engineer' is ideal as a team-leader, able to coordinate and supervise the activities of several specialists (Mechanical Engineers, Electrical & Electronics Engineers, Control Engineers, Software Engineers, Machinists, Fitters & turners, welders, etc.) to work on the design, manufacture, assembly and testing of a complete solution, such as a complex automation system, a new high-tech mobile robot or robotic manipulator, or a new kind of machine.