Computer Science Education - Science topic

Integrating Artificial Intelligence (AI) into computer science education is a topic of great importance.

In summary, integrating AI elements into computer science education can empower students to navigate the evolving landscape of technology and contribute to practical applications across various domains.

1. https://www.datacamp.com/blog/how-to-learn-ai

2. https://www.coursera.org/courses?query=artificial%20intelligence

3. https://www.computerscience.org/resources/learn-ai/

4. https://www.theknowledgeacademy.com/blog/artificial-intelligence-vs-computer-science/

Here are some of the top journals on computer science education and educational technology:

For me some basic knowledge of formal systems is essential for undergraduate CS students, as this is a necessary part of the scientific education.

If not, you might still learn a lot about software construction, but you wouldn't know nor understand its bedrock.

In addition to Rudra Tiwari perfect response, i think there is need to encourage more 'Social Integration' among the populace. The world is fast evolving and becoming a global village and there is need for everyone join the train. There is need to turn down the believe that education is a scam, technology will end cultural heritage and/or encourage crime by giving access to education(rural areas) through public enlightenment among other.

Dear Prof. Meriyem!

I did search for YOU resources you might well consider as value-added for your work:

1) Mouza, C., Mead, H., Alkhateeb, B. et al. A Virtual Professional Development Program for Computer Science Education During COVID-19. TechTrends 66, 436–449 (2022). https://doi.org/10.1007/s11528-022-00731-y, Free access:

2) Chrystalla Mouza, Diane Codding, Lori Pollock, Investigating the impact of research-based professional development on teacher learning and classroom practice: Findings from computer science education, Computers & Education,

Volume 186, 2022, Available at:

3) Garcia, I., Pacheco, C., León, A., and Calvo-Manzano, J. A., Cadxela: An educational tool for supporting the global software engineering education at undergraduate level, Comput. Appl. Eng. Educ. 2022; 30: 708– 729. https://doi.org/10.1002/cae.22482, Available at:

4) Yildiz Durak, H., Flipped classroom model applications in computing courses: Peer assisted groups, collaborative group and individual learning, Comput. Appl. Eng. Educ. 2022; 30: 803– 820. https://doi.org/10.1002/cae.22487, Available at:

Yours sincerely, Bulcsu Szekely

Infrastructure and technology readiness... Arvanitis, S. (2005). Computerization, workplace organization, skilled labour and firm productivity: Evidence for the Swiss business sector. Economics of innovation and new technology, 14(4), 225-249.

Hi proffesor Damian,

I've seen you have expertise in wavelets and mammography. I'm undergraduate student and I'd be thankful if you recommend me a way to enhance or detect microcalcifications (MCC) in mammograms with DWT. I'm trying with wavelet decomposition at 3 level with Db1 and hard thresholding with Donoho Threshold for subband denoising, but I don't get visually good results, this is to say, it doesn't see the MCC clearly

YES Tobias ... do not forget paradigms ... they can help you in your investigations.

Precisely, look at the indexes of use of programming languages (tiobe index for example) ... the evolution of educational programming languages must be particularly interested in the paradigms of these programming languages.

https://www.tiobe.com/tiobe-index/

How to explain the rank of the C language? (procedural paradigm ..) Why python is widely used? (object paradigm). is it the object paradigm that explains the use of this language !? or quite simply, it is more used by non-computer scientists where the principles of the object paradigm and strong typing are completely ignored?

Good luck !

Good Answer iliasse Hassala

Hi. I think you can use a lot of tools according to circumstances:

LMS (with password for your students) in case of official courses and for limited number;

Website (containing all course program and some quizz, with external links for technical tools and usefull softwares)+using e-mail/other ICT for continuous contact and eventual questions;

MOOC for fast courses for large public+using e-mail/other ICT for continuous contact and eventual questions;...

Good luck.

Hi, Cyril, there is a good explanation that you can find here:

https://math.stackexchange.com/questions/1359770/why-does-the-division-algorithm-work-for-converting-between-number-bases

Information and Cibersecurity are key areas that were not part of the traditional CS degree but most schools are now incorporating into the curriculum.

If you do research into CS education, you are not just choosing subject or topic, you should explore what is the best way to teach that topic, look for evidence of learning, or for problems that need better instruction or approach.

A big chunk of CS education research looks at how to help novice programmer to get the skills, or for evidence of learning in other key areas such as software engineering, as well as the need for soft skills, motivation, peer work. The use of MOOCs, feedback, intelligent tutors are other popular topics

Hope this helps!

Dear Jerry,

If I understood it well, you are in favor of teaching deductive, inductive,and abdutive  logic to children once they enter primary school. You continue and say that grammar and rhetoric (writing, and to a lesser degree verbal presentation) are taught almost as soon as a child enters school and continue throughout school. I agree with you that  grammar, writting, and to a lesser extent verbal presentation can be taught once children enter elementary or primary school. As for rethoric, I have some doubts that that can be the case. Note that rhetoric often appeals to idiomatic language, that is, a language that uses, say, style's figures, such as metaphors, hyperboles, metonymy, and the like. As a developmental psychologist I never saw a 6-year-old child to spontaneously use, in his/her spoken or written language,  metaphors (e,g., my father is in the spring of his life)  or hyperboles (e.g., my father was smoking a thinker cigarette).

Before addressing the issue at hand, that logic is not taught to children from an early age and this should be the case, let me clarify the differences among deduction, induction, and abduction,

Deduction or deductive reasoning allows us to derive b from a only where b is a formal consequence of a. In other words, deduction derives the consequences of the assumed premises. Given the truth of the assumptions or premises, a valid deduction guarantees the truth of the conclusion. For example, if p (John is at school) then q (Mary is also at school); p is the case (John is at school). Hence, q follows necessarily (Mary is necessarily at school). As you certainly know this is the logical argument known as Modus Pollens. Deductive reasoning is also at stake in Modus Tollens: Not q  is the case (Mary is not at school).  Hence, not p  has to be is also the case (John is not at school either). Correct hypothetical-deductive reasoning is also necessary to solve Denial of Antecedent  problems:  Not p Is the case (John is not at school). Hence, nothing can be concluded about q (it is not possible to draw any conclusion about Mary being or not being at school).  Correct hypothetical-deductive reasoning is also necessary to solve Affirmation of Consequent problems: q is the case (Mary is at school). Hence, nothing can be concluded about p (it is not possible to draw any conclusion about John being or not being at school).

Induction or inductive reasoning allows us to infer b from a, where b does not follow necessarily from a. A might give us very good reasons to accept b, but it does not ensure b. For example, if all swans that we have observed so far are white, we may induce that the possibility that all swans are white is reasonable. We have good reasons to believe the conclusion from the premise, but the truth of the conclusion is not guaranteed. Indeed, it turns out that some swans are black. Induction lies at the heart of many experimental studies.

Abductive reasoning or abduction is a form of logical inference which starts with an observation, and then seeks to find the simplest and most likely explanation. In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. More precisely, abduction or abductive reasoning allows us to infer a  as an explanation of b. As a result of this inference, abduction allows the precondition a to be abduced from the consequence b. Deductive reasoning and abductive reasoning thus differ in the direction in which a rule like "a entails b” is used for inference. As such, abduction is formally equivalent to the logical fallacy of Affirming the Consequent because of multiple possible explanations for b. What follows is an example of an incorrect solution for affirmation of consequent problems : “q is the case ( Mary is at school), then p is also the case (John is also the case, which is an incorrect conclusion). Consider now the following example of abductive reasoning In a billiard game, after glancing and seeing the eight (or black) ball moving towards us, we may abduce that the cue ball struck the eight ball. The strike of the cue ball would account for the movement of the eight ball. It serves as a hypothesis that explains our observation. Given the many possible explanations for the movement of the eight ball, our abduction does not leave us certain that the cue ball in fact struck the eight ball, but our abduction, still useful, can serve to orient us in our surroundings. Despite many possible explanations for any physical process that we observe, we tend to abduce a single explanation (or a few explanations) for this process in the expectation that we can better orient ourselves in our surroundings and disregard some possibilities.

There is accumulated  evidence that shows that 5 to 6-year-olds are already capable of solving Modus Ponens problems and that 8 to 9 year-olds are already capable of solving Modus Tollens problems. However, the literature on the four logical arguments also shows that such solutions are based on what is called a matching bias procedure, not on correct hypothetical-deductive reasoning. In other words, in if p then q statements, children tend to say, for example, that if John is at school, Mary is also at school; if Mary is not at school, John is not at school either; If Mary is at school, John is also at school; and if John is not at school, Mary is not at school either.There is also accumulated evidence that shows that even adults often fail while solving Denial of Antecedent problems as well as Affirmation of Consequent problems.

There is also evidence that shows that only formal thinkers in Piagetian terms are  capable of designing an experimental study or research.

All these considerations show that it does not make much sense to teach inductive, deductive, and abductive logic to children once they enter elementary school. Unless, that is, we take rote learning for true understanding.

I hope I has got your point and that this is of some help for you.

Best regards.

It is extremely pleasant to see that students now have started becoming concerned about what exactly their interest in EE is ! There are two questions in your message:

i) Why should one go for higher studies/research in his/her area of interest? Advancement in Technology is a never-ending process particularly from applications point of view. So, we see a rapid change in the way how technology is making our life easier. All this fruits are as a result of envisaging and realizing novel solutions. So, to summarize:

Higher education -> (should lead to) Enhancing research expertise -> (which should ultimately map to) -> Using Technology for human welfare

ii) Future aspects of these (mentioned) branches?                                                  IMHO, future of ANY (and EVERY) branch is bright iff we have genuine interest in that particular branch. Why? Because, if I have original interest in a particular domain, I would be able to think beyond constraints. The more interest I have in an area, the broader the horizon is. Just my thoughts.

Hi Marife,

You can see this video for more details

Regards,

Sameh Mtibaa

I taught beginning, intermediate and advanced programming for several years and one flaw that I have seen during this time is trying to isolate learning by modules. While module assessment is useful for learning, programming progresses in an incremental fashion. My approach was to have the evaluations divided into module(had to do it because of departmental requisites), module comprehension on top of previous material and problem solving and troubleshooting sections. At the end of each course (even introduction to programming) the students needed to hand in a project of complexity commensurate to the course level.

I have found from working in the industry that graduates who come seeking work based on module based programming learning to come with huge deficiencies in understanding problem solving. They know the syntax but do not know how to solve problems.

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@ Stefan: Thanks for reminding me about this discussion stream :). The conference is a bit far away for me but I have now written up my experience in form of a "Working Paper" which is available here:

 Computer Science, in my view, is an area that demands sound exposure to mathematics. However, with simulations and open source tools there is scope for pursuing computer science education to certain extent ( I am afraid not fully) with little exposure to mathematics.  

@Mehmet:

If the programming language you use is Scratch (https://scratch.mit.edu/hoc/) you could analyze the projects developed by the students with Dr. Scratch (http://drscratch.org/), a static code analyzer for Scratch projects that assigns a computational thinking score.

You can learn more about how to use Dr. Scratch for assessment here: https://www.researchgate.net/publication/281714025_Dr._Scratch_Automatic_Analysis_of_Scratch_Projects_to_Assess_and_Foster_Computational_Thinking

Good luck with your HoC activity. Best,

Jesús.

Eamon, it depends on how much management you want to place in the hands of the students, and which technology stack you are having students program with.

For example, with pure AWS/EC2 students can manage the entire process of configuring, packaging, deploying and managing VMs. The benefit here is that the VM they deploy can be running any stack they choose; the drawback is that there is a lot to configure and manage before they have a running app/service on the cloud.

In contrast, something like Cloud9 w/ Azure, or Heroku, makes deploying VMs a non-issue. The focus instead is on the app being built, and students use automated tooling to package and deploy their apps to the cloud. The benefit here is that students get to focus on the application, rather than the details of VM management; whether that is a drawback depends on you and the students.

With undergraduates, I encourage the use of the Ruby stack to build apps and services (with Sinatra and Rails) because of the rich framework API. I then have them deploy to Heroku, which I personally feel is fantastic, and students get lots of satisfaction.

You can let the advanced students use whatever cloud vendor and technology stack they want. (eg. encourage them to try Docker).

Also, I recommend Fox, A., & Patterson, D. (2012). Engineering Long Lasting Software, which was also available as an online course a while ago, maybe it still is.

An example that can be usefull is here:

Maybe you can teach a advanced topic in set theory.

Regards, Everthon Oliveira

Elena, first I think you must define what exactly you mean by evaluating the learning of software programming. In Primary School, as in other levels of school, you cannot base a curriculum solely on software. How would software learning fit into the program. For example, there are some excellent programs which help students to learn ABCs, to learn numbers, shapes, etc., through practice. Content subjects are really not appropriate until 4th grade (student 9-10 years old), because this learning requires sound reading and numerary ability for readiness.

Thanks for your interest, but gamification is not a motivational model.

It is an implementation (application) of method that attract in some manner USERS (someone).

We work on, measuring student's motivation in our Universities, so we need at least a theoretical framework as starting point.

although it should ideally be "research driven", there are alternatives...for example, if you have large data sets.that can be "mined" for the content they have hidden within them (e.g., by using cluster analysis or other data mining techniques)...obviously, it's not that simple, but they are both places to begin your search...good luck... 

As mentioned only motivated persons can produce and published scientific research in the academic environment. It is a hard job to produce regularly novelty, with enough contribution for the scientific community, impact in the society or industry, and present it in a way that is interesting for the other researchers and for the publishers.

In my opinion, who is really motivated by money usually stay far away of the universities as they do not pay (also cannot) the hours of work you need to achieve (and I underline again here) high levels of novelty, contribution significance and interesting work.

The universities give the scientific environment, the scientific nets, the equipments (labs), the assistants, the computers and software, libraries, inside culture and knowledge, and so on. This is very expensive to build and keeping it along generations as well as maintaining a permanent improvement, beside the serious teaching contribution for which is possible to a university to stay alive within reasonable costs.

I know very few about the universities in third world. Anyway, would recommend to check the payments (are they receiving a dignified wage, i.e. a full-time job must allow to keep a family with kids at university) , to check the number of hours of teaching duties (a very good university lesson is also a hard job, which require preparation, adaptation and a lot of energy which must be balanced between research and teaching) , to check the working conditions given at university, check if they have freedom to study the problems they want or they consider the most important (one must believe in the importance of the work being doing), check the mentioned tolerance to failures, and to check for the access given to the international scientific community as well as to the society.

Universities should invest some of their budget in inviting senior recognized scientists to stay for some periods, to evaluate the environment , transmit experience and their way of working in the field. Young talented future candidates will enrich a lot contacting recognized scientists that are interested in working with these junior fellows.

Of course, with globalization many of sharing opportunities are being closed by the extreme competition and commercialization. Many available knowledge where in the past easily passed from university to university, but not nowadays.

Also, removing responsibility of seniors on preparing future generations to replace them as a natural event when they retire is doing damage. Of course, retirement income should also be a dignified.

Finally, this express only an opinion at this moment which can be changed with discussion and reflection, but hope contribute for the discussion in this very complex subject.

Well, yes. But, assuming the students have basic knowledge of computer science. Because, stackoverflow most of the times avoids discussion on knowledge and stresses more on specific problems.

I mean, your answer is most likely to be closed if you ask 'How to bubble sort in Java or python?' But, if you face some issues of efficiency, edge cases, your answer might be accepted. You have to take not of this.

I feel, it can be advanced educational tool for students.

Natural language can be used with amazing precision - but most of us don't, at least not most of the time. Precise thinking, however, is absolutely required when learning to program. Python vs. Java may be more about the fluidity of the experience and the burden towards minimal viable programs. Those aspects do affect the learning curve.

When it comes to the use of precision when applying natural language, we need to tread a little carefully. There are two cases that I've seen: folks that use natural language sloppily because their use of language is a reflection of their style of thinking - imprecise and logically disconnected. Learning to program in such cases is somewhere between a possible cure and impossible. But there's also a significant part of the population that is hampered by working in a language acquired relatively late and far from their mother tongue or affected by medical conditions, neither of which necessarily reflects on the sharpness of their thought processes. So, jumping to conclusions in this area is highly problematic. (I am not at all implying that this is something implied by the original question!)

To conclude, I think we need to understand what exactly it is that accelerates learning of programming and how natural language skills (or the lack thereof) relate.

I agree with Jerold: teaching algorithms should not be confined to a particular programming language, and presenting algorithms in pseudo-code is the right thing to do.

My comment is that teaching algorithms should go in parallel with teaching data structures. Students should understand the complexity of the algorithms, which almost always depends on the underlying data structure. Most undergraduate and graduate textbooks ar not only about algorithms, but about algorithms AND data structures.

For example : http://classroom.jc-schools.net/la/activities/pptresources.html

http://presentationsoft.about.com/od/classrooms/ - Lessons

Logic gates can be implemented using the basic analog components, resistors, diodes, bipolar junction transistors and field effect transistors. All digital logic gates OR, AND, NAND and NOR can be implemented using switches however the behavior of these gates also can be achieved from the basic components. Logic gates can be performed using RTL, DTL, TTL, MOS and CMOS circuits.

I have just been to the ACE2013 (Advances in Computer Entertainment) workshop on "Tinkering in Scientific Education" and I think the ideas discussed here might be of interest to you.

We had a 21 day workshop on embedded control systems at our company for a group of students who had finished 2 years of engineering. They learnt sensors, filters, PID controller tuning and did a hands on Matlab/Simulink, Labview, and aurdino boards. They enjoyed it and learnt a few things. As an exercise I had given them a sealed plant model. They had to analyze and design a controller for this.

There's one piece of data from my university that I haven't seen in any discussion about MOOC's yet.

Our university has one course with about 11 sections for first-year students. The order that the sections fill is 1) Monday-Friday sections, 2) Saturday and Sunday sections, 3) the on-line section. The on-line section is even less popular that the weekend sections. Students have voted with their feet -- they want a traditional learning environment...at least for first year.

For upper level courses (after students have developed university-level learning skills?), on-line courses have more popularity. Thus, I see MOOCs adding value to the mix of university offerings, but that there is still value to the traditional campus environment -- especially for younger/newer students.

I forgot to say that the section “Transistor-Transistor Logic (TTL)” is from 4th edition of Sedra/Smith’s “Microelectronic Circuits” (see also attached file):

Adel S. Sedra and Kenneth C. Smith, Microelectronic Circuits, 4th ed., Oxford University Press, 1998.

This section is not included in newer editions of this textbook:

Adel S. Sedra, Kenneth C. Smith, Microelectronic Circuits, Fifth Edition, Oxford University Press, 2003.

Adel S. Sedra and Kenneth C. Smith, Microelectronic Circuits, 6th edition, Oxford University Press, 2009.

There are several popular problems for backtracking, like Eight Queen, etc.

Does someone need to know how an automobile engine works to drive a car? No. Does a mechanic have to have a degree in mechanical engineering to repair a car? Again, no. Computer systems, like cars (and other technologies), have layers of abstraction that are relevant to a particular user -- and even the same user may have relationships across multiple perspectives (e.g., an automotive designer who likes to change the oil of his car and then drive to the store). The vast majority of computer users have no idea how it works -- and they are quite successful. The question here may be better focused on the levels of abstraction that drives hardware and software construction.

You may learn those in the rental basic like cloud backbone... :)

Very good question, Mudasir. I happened to come over a European technical report with a questionnaire relating the developmental complexity of a Web project. From resulting metrics they could tell you, whether you should use a 'long' or 'short' lifecycle, another term for money spent, IIRC. The whole process was called e-minder. Maybe you can find this online, before I spot it in my papers.

The Art of Proof :Basic Training for Deeper Mathematics by Mathias Beck and Ross Geoghegan

I agree with Milan Tair who provided the correct answer for this question. Younger students have grown up in a world where results from their efforts are nearly instantaneous (like video games) and does not require weeks or months to find the solution to a problem. Students are living in an environment that does not mention or acknowledge the fact that patience, and discipline, along with subject-area knowledge is required for CS/IT, engineering, mathematics, and science endeavors. Some people obtain great satisfaction from solving a problem after many months or years of working on it, but most people become frustrated easily and give up, seeing no use to continuing work until a solution is reached. To those people, the problem cannot be solved quickly and it is a 'waste of time' to continue (they get bored easily).

Also, critical thinking skills are required (which goes beyond rote memorization), which discourages most people from even attempting these subject areas. One thing I have learned is that every significant problem (especially programming-related problems) I have every solved in my career has taken me anywhere from 1 to 6 weeks of concentrated effort to complete, but I see this as an enjoyable challenge and a test of my knowledge, skills, and abilities, where others do not understand why I enjoy the challenge. We need to find and encourage those students who want to develop the patience and skill required to solve computer science problems.

I performed few workshops for kids aged 10-15 with GameMaker. Within one hour when properly guided they are able to create one room game, simple but working, and meantime learn concepts like sprite, object, collision, event, action, etc...

I also met some of them that were continuing work at home, with quite interesting results.

You will find more at: http://yoyogames.com/education

I do not know Scratch, but in last wourkshops group I had some kids talking they were learning it. And still they were amazed by results coming from GameMaker.

Wilfried, is my water the same as your water?

Of course our minds are different. I'd like to define understanding

(here: of a word) as activation of the appropriate concepts.

There is also a measure for evaluating how well this is done.

Attached are two semantic maps. The left one is my notion

of water, the right one that of another person (might also be

in the mind of a computer). I expect that when I say "water" the

other person activates "swimming", "ocean", "drink" and so on.

How strongly other words (symbols, concepts) are affected

depends on the semantic distance of the word to the center.

The other person, upon hearing "water", will also activate

nodes in his semantic network. Every understanding of

a word is paired with a unique activation pattern, activations

of related words. How well these activation patterns match

among two persons is a measure for how well the communication

partners understand each other

Regards,

Joachim

I work with STEM to STEAM. Just completed two projects with undergraduate students (including math and science majors) as well as students in the humanities. We did small robotic/kinesthetic sculptures for one project, looking at the physics/motion and links between motion and aesthetics. The next project was animation where students chose which form of animation to use, incorporating a range of animation platforms, low and high tech. This summer I'm going to learn arduino and start introducing basic programming into my visual arts courses.

For Java, Python, C++, and a few other languages, we use Web-CAT (http://web-cat.org/), which is one of the most widely used open-source tools specifically for program grading. For C, assembly, and other low-level programming, it doesn't offer plug-ins so you can't use it there without doing some work.

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Hi Rens,

VCC is focused on software correctness, one aspect of which is security. Most practical security problems are really problems of program correctness (buffer overruns being the best known example); if you don't prove things like memory and concurrency safety, anything else you "prove" about the system is moot. Moreover, one typical way to prove security of a program is to prove that it correctly implements a deterministic specification.

There has also been some security-specific verification work with VCC. In particular, there has been work on verifying software that makes essential use of cryptography, as well as some work on proving information flow for C code. You can contact me out-of-band if you want more details.

cheers,

ernie

PS the proper reference for VCC is vcc.codeplex.com.

I guess this is a general all time hot topic. well known technique such as LOC, Function Point, and COCOMO models all have been well established. I think there is lot of research to be done on experience based metrics where domain knowledge and skills are required. How do we develop a tool? Also, I recently seen an article exploring FP for new technology projects such as cloud and SOA. This is an interesting article. I think we should form a small working group and we could contact Berry Boehm who is the pioneer in cost estimation methods. FP links http://www.servicetechmag.com/I68/1112-4