Quantum computing presents a paradigmatic shift in the field of computation, in which unintuitive properties of quantum mechanics can be harnessed to change the way we approach a wide range of problems. However, due to the mathematics and physics perspective through which quantum computing is traditionally presented, most resources are inaccessible to many undergraduate students, let alone the general public. It is thus imperative to develop resources and best-practices for quantum computing instruction accessible to students at all levels. In this paper, we describe the development and results of our Massive Open Online Course (MOOC) "Introduction to Quantum Computing for Everyone." This course presents an introduction to quantum computing with few technical prerequisites. In the first half of the course, quantum computing concepts are introduced with a unique, purely visual representation, allowing students to develop conceptual understanding without the burden of learning new mathematical notation. In the second half, students are taught the formal notation for concepts and objects already introduced, reinforcing student understanding of these concepts and providing an applicable context for the technical material. Most notably, we find that introducing the math content in the curriculum's second stage led to no drops in engagement or student performance, suggesting that our curriculum's spiral structure eased the technical burden.
Quantum computing presents a paradigmatic shift in the field of computation, in which unintuitive properties of quantum mechanics can be harnessed to change the way we approach a wide range of problems. However, due to the mathematics and physics perspective through which quantum computing is traditionally presented, most resources are inaccessible to many undergraduate students, let alone the general public. It is thus imperative to develop resources and best-practices for quantum computing instruction accessible to students at all levels. In this paper, we describe the development and results of our Massive Open Online Course (MOOC) "Introduction to Quantum Computing for Everyone." This course presents an introduction to quantum computing with few technical prerequisites. In the first half of the course, quantum computing concepts are introduced with a unique, purely visual representation, allowing students to develop conceptual understanding without the burden of learning new mathematical notation. In the second half, students are taught the formal notation for concepts and objects already introduced, reinforcing student understanding of these concepts and providing an applicable context for the technical material. Most notably, we find that introducing the math content in the curriculum's second stage led to no drops in engagement or student performance, suggesting that our curriculum's spiral structure eased the technical burden.
Investments in quantum technologies, which are based on the effects of quantum mechanics, have escalated in recent years, with big players such as IBM, Google, and Microsoft engaging in the race for quantum supremacy. Some potential benefits of this cutting-edge technology include developing new drugs and materials through accurate molecule simulation, establishing more secure and reliable communication channels, and finding faster solutions for complex optimization problems. As quantum technologies evolve, however, the demand for new software, interfaces, and end-to-end systems to properly program and explore the advantages of quantum mechanics becomes paramount. This requires engineers, especially software engineers, and computer scientists, to have multidisciplinary knowledge and skills. Unfortunately, introductory quantum computing and technologies courses are mostly available in physics, and most engineering and computer science courses do not have modules on quantum physics, leading to a talent gap in the current job market. Therefore, this paper proposes a short teaching plan for introducing quantum computing to students with a more technology-based background, such as computer science and engineering students. This plan uses active learning methodologies, such as Challege-Based Teaching, to better engage these students and contextualize the many applications of this new technology. The initial teaching plan consists of a 3-hour seminar introducing the main quantum mechanics concepts and the technology applications, a 3-hour introduction to the math fundamentals and quantum logic gates, and a 3-hour handson workshop using the IBM Qiskit platform. Two versions of this plan were executed in two different moments: (1) a one-day event open to undergraduate students from different institutions and backgrounds, and (2) a 3-day internal training course for computer science and information technology management undergraduate students from our higher education institution. Data was collected during both events through online forms and interviews to measure the learning outcomes of the produced material and better understand the public interest in the field. The results identified key elements for better teaching quantum computing for computer scientists and engineers, providing guidelines for developing a more extensive and term-long teaching plan for undergraduate technology courses.
As quantum computers are becoming available for experiments, their enormous potential is being recognized among college communities. The goal of introducing quantum computing in college level computer science programs is becoming attractive. However, this goal comes with opportunities and challenges. of the challenges is that quantum computing appears to require substantial background in physics as well as in computer science. However, it is hard to convince students to major in these two fields. Computer Science students with a minor in physics can also be considered. Several alternative curriculum structures are possible. A non-consecutive two-course framework is proposed here. A course on Introduction to Quantum Computing may be offered to sophomore level students. This introductory course may teach fundamental ideas about quantum computing with basic concepts behind BQP (Bounded Error Quantum Polynomial) and related topics. This introductory course may be followed up by some physics courses (on related topics such as quantum mechanics) and some computer science courses. Then, a senior level course on Advanced Quantum Computing may be offered that may include some well-known algorithms (such as Shor's Algorithm for Quantum Factorization and Grover's Algorithm for Quantum Search) and their implementation and practices on some simulators (such as QuIDE from http://www.quide.eu/) or some prototype quantum processors (such as IBM's prototype quantum processors). For advanced level courses, some course materials are available from various sources (such as MIT OpenCourseWare). The greater challenge would be in teaching the introductory course mentioned earlier that motivates students towards investing time and efforts in learning quantum computing and related physics, math and computational topics. The challenges of teaching the introductory course should not be underestimated. Some flexible strategies can be suggested for this course so that the biggest challenges can be overcome. Some initial assessments of the students may help adjusting the introduction strategies with student's preparation. What is recommended is that the instructor should be able to adjust the coverage of topics, rigor and depth of treatment. That is, the introductory course should not be rigidly defined. It should be recognized that the main emphasis of the introductory course is actually instilling motivations and curiosity in student's mind about potentials of quantum computing through adaptive teaching of some selected topics where traditional digital computers do not provide tractable solutions. Ideally a balance could be achieved among aspects of depth of treatment, rigor, inspiration, motivation and coverage of topics. Students should be able to realize that the emerging quantum computing technology would be able to provide elegant solutions to some of the classical intractable problems combining ideas from physics, math and computer science in an innovative way. One size fits all is not a good approach and discussion of issues may help us face the challenges better by pragmatically considering a range of possible alternatives. Resources that are currently available may also need to be reviewed for the purpose of introducing quantum computing adequately.
Quantum computing will likely change our world as we know it today. In bringing together fields such as quantum mechanics, mathematics, and computer science in their construction and application, quantum computers hold a promise of tremendous increase in processing power when compared to present day technology. For an educator, teaching this topic requires that consideration be given to the fact that quantum computing is not only based on hard-to-teach aspects of physics, math, and computing, but that quantum computing itself is still in the early stages of its development. What is certain is that concepts such as Shor’s and Grover’s algorithms have already been developed specifically for use with quantum computing. Both algorithms are the beneficiaries of quantum properties such as superposition and entanglement which are at the core of the new technology. This paper is presented in a bottom up structure starting with the explanation of the basic component, the qubit, before moving to superposition and entanglement and ending with a lucid explanation of both of the algorithms. Due to the complex nature of the topic, teaching this subject requires that certain measures be taken to teach all students at all levels and have them feel comfortable within themselves about the topic. The course is meant for anyone who wants to learn quantum computing. It is furthermore recommended that those attending have a blank slate so we start with new students. We would like to see a variety of students taking and passing the course, with that in mind, the explanations of the topics are done without employing an excessive amount of math common to other courses in quantum computing. The recommended approach for teaching is through the use of videos and a curriculum which is broken down so topics are made more general and the discussion of that effort is the main focus
Quantum computing has emerged as one of the most influential technological developments of the twenty-first century. While considerable attention has been devoted to hardware development, algorithm design, and industrial applications, comparatively less emphasis has been placed on the educational challenges associated with introducing quantum concepts to engineering students. Most available learning resources are designed primarily for physics students and often require prior knowledge of advanced quantum mechanics. Consequently, engineering students frequently encounter significant conceptual barriers when attempting to understand quantum computation. This chapter presents a mathematics-first educational framework aimed at simplifying the learning process for engineering students. Instead of introducing quantum theory through wave mechanics and advanced physical interpretations, the framework begins with familiar mathematical concepts such as vectors, matrices, probability, and linear transformations. The chapter demonstrates how core quantum concepts can be taught using accessible mathematical tools already encountered in undergraduate engineering curricula. A structured educational model is proposed and illustrated through practical examples, matrix operations, simple quantum gates, and engineering-oriented learning activities. The framework is intended to reduce cognitive barriers, improve conceptual understanding, and encourage interdisciplinary learning among future engineers. The chapter further discusses potential applications of quantum mathematics in thermal engineering, computational fluid dynamics, optimization, artificial intelligence, and advanced manufacturing.
Abstract Quantum computing is a rapidly developing technology, and we are experiencing an urgent need for experts in the field. However, there is a lack of traditions, research, and development on to what extent, and how, information technology students without a background in physics should be taught quantum physics. This paper contributes to the field by suggesting key topics in a course for information technology students on the master’s level. We have identified a core content of eight key topics, ranging from content purely from quantum physics and the formalism of quantum mechanics to its use in quantum algorithms and coding. The proposed content forms part of a master’s course developed for information technology students at Oslo Metropolitan University, Norway. By means of group interviews and questionnaires to students, the students’ experiences of the course are investigated. Results indicate that information technology students are capable, and interested in, learning quantum physics for the purpose of education in quantum computing. An integrated approach, where students learn quantum physics and quantum computing in the same course is found to work well for most students. However, as the challenge is extensive for some, it is important to make the purpose of each component of the content clear.
The quantum computing curriculum developed in the Freshman Research Initiative at The University of Texas at Austin caters to students who have not yet studied advanced math and science. We lower the barrier to entry by simplifying notation and teaching through application of the concepts, only covering math methods as they become necessary. Physical motivation and simulation connect with students, and embedded examples and practice problems help cement their understanding. Through learning to program in Python and completing creative technical projects, students gain valuable, transferable skills while exploring quantum information and computing.