Characteristics of a Good Learning Environment Free Essays

Qualities of an astounding learning condition. The physical spot of the homeroom can influence an understudies learning. I saw that numerous homerooms are formed like a container. We will compose a custom article test on Qualities of a Good Learning Environment or on the other hand any comparable point just for you Request Now In which the educator remains at the front giving the understudies data, instead of information. Study halls ought to be structured with the goal that the educator and understudies can meet as a gathering, also have the option to work freely. The technique that I discover works the best is when understudies cooperate as little gatherings. Data can be better analyzed and be clarified in alternate points of view. Understudies need magnificent teachers in their homerooms. Educators make a characteristic basic learning condition for their understudies. Each instuctors condition will be distinctive in some kind of way. A few educators make this condition with talks, conversations, or pretending. These kinds of instructing will assist understudies with learning new material and apply it in their lives. Commonly an instructor’s address is very long, and I lose intrigue. I regularly take a gander at the clock or dream sooner or later. It’s not on the grounds that I don’t care what their discussing, it’s simply that I appreciate working hands on. Educators assume a significant job in a student’s achievement and should instruct such that understudies best learn. The job of evaluations is a significant piece of assessing an understudy. An understudy who tries sincerely and invests a great deal of energy will typically procure passing marks. The understudies are anxious to learn new material and apply it. Me, myself regularly endeavors to procure passing marks. Ordinarily I don't get my ideal evaluation in light of the fact that multiple occasions I sufficiently do to get by. I regularly get disappointed with myself for not accomplishing an evaluation I could have earned. Learning is my main job and obligation as an understudy. In the event that I neglect to learn it who will learn it for me. I must be 100% committed to learning new things. I realize that each class cap I am going to in school will be applied in my profession. I realize that I am a long way from being a decent essayist however I’m ready to figure out how to get one. I will likewise figure out how I could have composed this article better from my educator. Step by step instructions to refer to Characteristics of a Good Learning Environment, Essay models

The Arrangement of the Genes Essay Example | Topics and Well Written Essays - 1000 words

The Arrangement of the Genes - Essay Example The main thing protecting us from them is our resistant framework. Our intrinsic insusceptible framework (for example skin, mucous layers, sniffling, flickering, discharge of waste, and so on.) is the person on call and is answerable for a large portion of the pathogens we experience regular. For the unprecedented pathogens, we depend on our versatile invulnerable framework to rapidly create and battle new and uncommon pathogens that the inborn insusceptible framework can't deal with. That aside, it additionally changes itself to be set up for a rehashed assault by a similar life form. It is astonishing to consider what number of hurtful living beings are repulsed over and over by this framework that ceaselessly changes to guard us. A portion of the key players in our versatile invulnerable framework are our T cell antigen receptors (TCR). They are ‘highly factor antigen-acknowledgment structures’1 whose activity is to perceive antigens and initiate the proper lymphocyte s to battle them. Since the TCRs are antigen-MHC compound explicit and insoluble simultaneously, disconnecting them was exceptionally troublesome until researchers begun utilizing clonotypic monoclonal antibodies.2 With this strategy, they had the option to confirm that the TCRs were heterodimers of 2 arrangements of chain qualities: the ?:? what's more, the ?:? chains. The two have comparative structures, however they identify various antigens. The ?:? is the most widely recognized (90-99%) while the ?:? is the minority (1-10%). 3 The previous distinguishes antigens gave Major Histocompatibility Complex (MHC) while the last doesn’t need MHC to recognize certain antigens. The hereditary structure of the TCR is like that of the immunoglobulins (Ig) in B cells. It is made out of Variable (V) and Constant (C) areas. The variable area contains Variable (V), Joining (J) and Diversity (D) fragments relying upon whether the chain is a light or overwhelming immunoglobulin (or a ? or on the other hand ?, or a ? or then again ? chain for a TCR). In substantial immunoglobulin chains, VDJ quality sections consolidate arbitrarily, while in the light chains (Lambda and Kappa), they just have V and J portions to join. Combinatorial relationship in B cells further expands changeability by enabling to make ‘any one potential substantial chain and any one potential light chain’ in all individual B cells.4 Because of the enormous number of conceivable quality revisions, the structure of Ig or TCR qualities i s for all intents and purposes special for every B or T lymphocyte.5 Figure 1 T-cell receptor ?- and ?- chain quality adjustment and expression6 Since T cells additionally have antigen receptors like the immunoglobulin, they likewise have a comparable procedure of quality modification and articulation. In Figure 1, we can see a ?- and ?- chain modifying and meeting up to frame a TCR. The ?- chain quality revamp is like the light chain since they don't have a D? to consolidate. The ?- affix is likewise like the overwhelming chain since it joins V?, D? what's more, J? quality portions. The less regular ?- and ?- affixes are fundamentally like the TCR?- and ?- chains, however with a couple of changes. The ? chain is found inside the TCR? chain, between the V? what's more, the J? quality sections. This course of action causes lost ? chain at whatever point the TCR?- chain improves, since any fragments in the middle of V? what's more, J? will be erased. The ?- anchor is like the TCR?- ch ain in that it has V, D, and J portions. The ?:? receptors are to a great extent a secret to researchers as of the moment.7 One of the couple of things resolved to be genuine is the way that they can recognize non-traditional significant histocompatibility complex class I particles T10 and T22.8 Combinatorial affiliation further builds the changeability, making it conceivable to have an interesting hereditary course of action for each T cell receptor. Figure 2 The quantities of human T-cell receptor quality sections and the wellsprings of T-cell

6-3

6-3 Its no secret that Course 6-3 (Computer Science) is one of the most, if not the most popular major at MIT. According to the Registrar, there were 757 undergraduate students alone enrolled in Course 6-3 for the Fall 2017 term. Thats roughly a fifth of the undergrad population (that declared a major)! So its not just a meme when people say that if you had to guess what course someone was, its probably 6-3. As such, Course 6-3 often has a fair bit of stigma as a sellout major, since its a) extremely popular and b) associated with a higher probability to earn above-average salaries after graduation. The fact of the matter is that pretty much all the people Ive met who are 6-3 (which is a lot) arent in it solely for the money. 6-3 is actually a fun  major believe it or not, and Ive gotten far enough along in it now to explain what its been like from my perspective. This post was motivated because Ive been corresponding with a prefrosh on Reddit that had a lot of really good questions about 6-3 that I didnt realize wasnt common knowledge becase Id been exposed to 6-3 for so long. So I thought Id make a fair, not but exhaustive, overview. Why is it 6-3 and not just 6? Course 6 (Electrical Engineering and Computer Science), at its heart, is broken down into three separate portions of a spectrum: 6-1, 6-2, and 6-3. 6-1 is pure EE, 6-2 is a hybrid of EE/CS, and 6-3 is pure CS. (Im being a little disingenuous to keep the spectrum analogy: theres also 6-7, which is CS/Biology, and 6-14, which is CS/Economics. However, 6-7 and 6-14 are named because 7 is biologys course number, and likewise for economics, whereas the numbers 1, 2, and 3 mentoined prior dont  refer to Course 1, 2, or 3.) Although its a spectrum, if you weight it based on enrollment, its lopsided towards 6-3: based on the same information from the Registrar, there were 59 people in 6-1, 380 people in 6-2, and 757 people in 6-3 as mentioned before. The fact that its called 6-3 doesnt mean that its a lesser major or a minor, its a full-fledged major that is one of many offered by the Electrical Engineering and Computer Science (EECS) department, which itself falls under the general School of Engineering. What classes do you take? First, lets go over the required classes. Most of this information is provided by the MIT Catalog. Sometimes, you will have to make a choice between two or so classes, like choosing between 6.045 and 6.046 or between 6.034 and 6.036. Feel free to refer to the Catalog for full requirements. If youre new to programming or computer science and dont know some terms as this section goes along, dont worry this blog post is meant to serve as an overview of the major, to give you a sense of whats to come. Notes: There is a possibility I give slightly outdated information for some classes since Im describing them based on the semester I took them, and not the most recent offering. I dont have an opinion on some of the classes, since I havent taken them: so I have several 2E (Next House) friends/alums who are/were 6-3 that will chime in in those cases! 6.0001 Introduction to Computer Science Programming in Python: This class is essentially what the title says. No prior programming experience is required yes, you can be a 6-3 without knowing anything coming in! You learn really basic things in the beginning, like declaring variables and setting them equal to numbers! Then you learn about lists, and tuples, and dictionaries, and functions, and recursion, and then finally you learn about classes and basic object-oriented stuff like inheritance. There are a few problem sets, and theyre comprehensive and long and will serve as the bulk of the class. Its six units, so if youre new to programming, taking four full classes plus this is a great start to your first freshman fall. 6.042 Math for Computer Science: Basically your discrete math class. Really useful, starts off by going over proofs and ways to construct them, then takes you on the tour of counting, graphs, probability, and other fun stuff. The art of constructing proofs are really the backbone of the entire course and you use the skill throughout, which is why its covered first. Its also taught using the flipped TEAL format, which means that you arent in a lecture hall but in a small group setting with around five other classmates. In addition, you learn the material outside of class and apply it in class by working on problems. 6.01 Introduction to EECS via Robotics: If you take this as a 6-3 and intend to go pure CS, itll probably be the most EE class youll take. 6.01 belongs in a trio of courses (6.01, 6.02, 6.03) that are intended to serve as introductions to the general EECS department. 6.02 deals with communications networks, and 6.03 deals with medical technology, but 6.01 deals with robots! When I took the class, there was a final exam, but last semester, it was replaced by a final project instead, which I think is great. 6.01 was broken up into four main modules that took you on a tour of EECS: signals/systems, circuits, (mainly Bayesian) probability, and (mainly graph search) algorithms. You do labs every week that revolve around a cute robot that will be able to do a surprising number of things by the time youre done with it, like follow an infrared sensor around, park itself neatly into a miniature parking space, and find its way out of an unknown maze just by sensing the walls around it! 6.004 Computation Structures: This was a really fun class, although it was also really hard! It takes you on a low-to-high level tour of a typical computational machine (otherwise known as well, a computer). You start by learning binary and how MOSFETs work, and how MOSFETs can be combined to make basic logic gates like ANDs, ORs, XORs, et cetera. Then you start putting the ANDs and ORs together to make some more complicated structures like ALUs (Arithmetic Logic Unit) or ROMs (Read-Only Memory). Theres an actual software program that you can use to build the gates and units yourself as part of labs and homework! Then comes one of the hardest, but coolest parts: you learn the parts of a basic processor, and build your own, called the Beta. After accomplishing this great feat, you get your own sticker your can put on your laptop that says Beta inside. :) Of course, youre not done there: once you have a processor up and running, now you need to know how to use it! Next up is assembly code, where you learn how binary is actually magical and how assembly code translates to actual binary, and then you learn how to wrangle all 32 registers you have to your advantage. Youll eventually be able to code a bubble sort algorithm using assembly. Youll also learn how to pipeline your processor. Then comes the high-level stuff: how caching works, how virtual memory works, how compilers work, how semaphores work and how deadlock happens, what kernels are and how to make your own really tiny OS, how to deal with multi-core structures. Finally, with all this newfound knowledge, youll be challenged to make your Beta run as fast as it can, in the form of a final design project. 6.UAT Oral Communication (CI-M): (i might be biased bc im a GTA for this course this coming semester) One of the most useful courses Ive taken at MIT. Really hones your ability to present and convey ideas efficiently and in an engaging manner. (Break the MIT stereotype that were all just awkward nerds who cant talk!) Your experience is highly dependent on your recitation TA/RI who give you feedback on how to be a better presenter. Tony Eng is a great lecturer and a really nice guy. Tbh would recommend taking this class not your senior year, it helps develop so many soft skills that you can use in other class presentations and interviewing and everything. (Laura P. 19) 6.006 Introduction to Algorithms: 6.042 used a lot of math, but this class was when I really felt like I was starting to put on my thinking cap, and the major went from programming all day all the time! to am I a math major? Instead of programming as the central focus of a class, 6.006 will rack your brain as most of the time you spend on problem sets will be thinking of the solution through lots of metaphorical pen and paper. Youll be in front of the keyboard to implement certain algorithms or type up your pset in LaTeX, but other than that, youll most likely be pacing back and forth (me), whiteboarding with other people in your pset group, or spending long nights at your desk wondering how the heck were going to get this pizza delivered in O(E+V ·log(V)) time. Taking this class during my sophomore fall was an interesting time for me, because a number of things happened: I was sick with a crap disease all semester, I was losing motivation trying to keep up with 18.100A (which ultimately led me to drop it and give up on Course 18), and my feelings for MIT in general were at an all-time low (senior house and its aftermath). In the end, I got a C in the class, which I didnt mind because I felt like I wasnt able to give that semester my best effort anyway, and I was okay with that. 6.006 reassured me that even though I wasnt going to pursue any form of a Course 18 major or minor, Course 6 offers more than its fair share of challenging you in the mathematical sense. Which leads me to 6.046 Design and Analysis of Algorithms: I thought 6.006 was hard. Then I had to take THIS class. Oh my god. Where do I even begin with 6.046. I can safely say that 6.046 picked me up, chewed me up, and spit me out drenched in dense, long proofs, esoteric definitions (I wish I could remember what alpha-convexity means), and hellish psets twice as hard as 6.006. That being said it was a good class because it pushed me a lot, and I was finally able to put in enough effort to where I felt a lot better with algorithmic thinking and proving things related to algorithms. I got a lot better at analyzing asymptotic time/space complexity, understanding harder algorithmic concepts like streaming algorithms and linear programming, and getting used to CS-based math in general. There was a fair share of referenced research done in recent decades, which was cool. There wasnt any programming, which I see as a downside since although I get the general concept of a given topic covered in that class now, Ill still have to put in a lot of effort in if I want to implement those concepts in the future. Also, the curve (read: grade cutoffs) was really good last semester, which gave me a lot of faith that the course instructors knew that the class was really hard. I absolutely got destroyed on the final (two full SDs below average) but managed to pass with a pretty okay grade, to which I say, heck yes. To all your friends that say Course 6 is an easy major, please tell them to look at 6.046. 6.045 Automata, Computability, and Complexity: Basically a sampler of 18.404 (Theory of Computation). Prof has changed, but I had Ryan Williams and he was amazing. Very different from most topics in cs, doesnt require you to have a background in anything, it teaches you a different way of approaching a very unique space of problems. Doing psets is almost like solving puzzles. (Laura P. 19) I can’t really say much about 6.045, but since 18.404 goes over similar material, just perhaps more rigorous and with more proofs, I would definitely recommend. It helps you understand better computing power, the limitations of computers, and sets the basis of why algorithms are important. (Alicia O. 19) 6.009 Fundamentals of Programming: Basically, you get a lot of (Python) programming experience through this class, and this experience is gained through long, educational labs. The Lisp interpreter lab was one of the most fun labs Ive done so far at MIT. Learning how to write a language (especially a cool one like Lisp) using another was just really cool! There were a lot of other fun labs as well: n-dimensional Minesweeper, autocomplete, and a platformer adventure game. :) The labs are probably slightly different now but youll get your fair share of labs you dont care for and labs that are actually pretty darn cool. 6.009 pairs into 6.031, and together they form what used to be 6.005, which doesnt exist anymore. 6.031 Elements of Software Construction: 6.031 is probably my favorite class tbh. Its hard as hell, theres a ton of work, but it was a class that made me go yep course 6 was the right choice. Theres nothing like finally completing a pset, looking at the cool thing you just made with your own two hands (plus computer lol), and just appreciating all the work you put in to get there. Like carlosh said, its definitely made me better at programming, and its How To Software (For Realâ„¢?) (Shavina C. 19) 6.031 is what I knew as 6.005, and it was one hell of a class to go through. They upped it to I think a 15 unit class which is just slightly more representative of the fuckload of work youll have to do for it. I struggled a lot with that class, especially because I had trouble transitioning from knowing only Python and being used to a syntactically lightweight language to something as obscenely verbose as Java. That being said, I am undoubtedly a better programmer as a result of 005, and its essentially How To Not Get Fired In Industry: The Classâ„¢. (Carlos H. 17) 6.033 Computer System Engineering (CI-M): Katrina and Chill. Probably one of my all around favorite classes. Katrina is such an amazing lecturer and youre doing yourself a disservice if you dont go to lecture. Its a CI-M so theres a lot of writing, which some people like to complain about but youre going to be an engineer whos going to have to write and be able to digest technical papers so that practice is welcome. YMMV by a lot with the final project. (Carlos H. 17) Despite being a CI-M, 6.033 has given me the most applicable technical knowledge out of any class Ive taken so far. (Cory L. 20) 6.034 Artificial Intelligence: Winston and Chill Part 1. Gives you a sampler buffet as Winston would call it, essentially brief history of where AI was, where it is now, and where itll be going with the Spiritual/Right Now lectures. Had probably my favorite grading mechanism re: tests, where the final had sections corresponding to each midterm you took, and your score would be max(midterm grade, final grade), so it was a essentially a second shot at your midterm. If you were happy with all your midterm grades, you didnt need to take the final, but if you bombed only one midterm then youd only need to do that section on the final. Didnt do too much in terms of giving you hot marketable ML skills a la 6.036, but was a chill way to satisfy that requirement (chiller than 036 imo but ymmv depending on whether you enjoy the 036 material). (Carlos H. 17) In addition to what Carlos said about 6.034, I really liked the “right now” lectures they do. Like every week, exception being in the beginning they don’t do it as much and at the end it’s almost every lecture, they invite an expert in a field of AI to talk about their research and the applications. I found them inspiring, and honestly a class is much more fun to take when you’re reminded of the end picture/have an answer to “but why are we learning this?”. Also you learn a lot about human intelligence, which you need to understand to do AI. (Alicia O. 19) 6.036 Introduction to Machine Learning: You can take either 6.034 or 6.036 to satisfy the major requirement. 6.036 deals a lot more with the how with respect to machine learning, and probably less of the why than 6.034. You will be *fairly* proficient with numpy (a Python library) by the time youre done with this class. The lecturer last semester, Leslie, is great and also was my freshman advisor so thats a double thumbs up for me when recommending this class. Youll learn a lot, too: from simple linear classification problems to regression, to simple neural nets, to CNNs, to RNNS, to MDPs, and more, this class has a lot of material. Youll be able to make your own neural network for your own projects. :) Those were all the required explicitly named classes, but theres a number of electives you have to take to round out the major, and once again we have people that chimed in with thoughts about classes theyve taken that are related to Course 6-3. Note: some of these classes wont count for the major since theyre in a different department, but theyre still cool classes! Also, this section is growing and more stuff should be updated by tomorrow or so. CMS.609 The Word Made Digital: When I walked into ‘The Word Made Digital’ on the first day, my professor (Nick Montfort) had the game ‘Everything’ pulled up on the projector, and proceeded to play around for about the first 15 minutes of class. He didn’t provide any real context, and he didn’t provide any introduction until he was done, but I already had a feeling I was going to like this class. Looking back, ‘The Word Made Digital’ was a little abstract, a little zany, a little technical, but definitely an all around engrossing experience. In the strict sense, the class looks to analyze non-narrative digital uses of text, using approaches from poetics and computer science. (link) But for me, it was a chance to really explore my creative side by using my technical talents. The class centers on 4 programs, each featuring a unique prompt, and each one giving me a chance to try out programming in an artistic way that I had never even considered before. Overall, the assignments were a really nice break from the concrete instructions of typical course 6 classes, and Prof. Montfort was an incredible resource who helped me think about the unusual and really put my skills to use. To date, this is one of my favorite classes I’ve taken at MIT. (Matt F. 20) Matts programs for the class can be found here. 6.813 User Interface Design and Implementation: You work one 1 UI project for the duration of this course in a group of 6, plus you have a series of psets building web version of candy crush. Good foundation for what defines good/bad UI/UX, kind of a freebie class as long as you turn in the work on time. After taking this course you likely will pay attention to the usability of things and call out the ones with bad UI. (Laura P. 19) 6.858 Computer Systems Security: Hands on security class. Every assignment in this class revolves around breaking systems and building even more secure systems, in a variety of languages. Theres never a correct answer, as long as you find the vulnerability holes and successfully break or fix the system. (Great class if you want that kind of hands on work around security, also it feels awesome when you break things LOL) (Laura P. 19) With a lot of those classes under your belt, do you think youre prepared to go into the industry? Oh god no. Far from it. Course 6-3 is mostly Python before something like 6.031, which means that if you need to learn other languages (to be more employable, to do non-Python projects, do web development) you need to learn a lot of things on your own. I came into MIT with not a lot of programming experience (Course 18 was more my thing). I knew some basic Java and that was about it. Since then, Ive gotten to be fairly proficient with Python, but not much else. Arguably, this is a bad thing, since youre limiting yourself to one language. But after thinking about it, I think exclusively working in Python for almost two years wasnt so bad after all. The exclusivity let me really get into Python and understand a lot about how it works, and how programming languages worked in general. This meant that I could learn other languages on my own much more easily. Im reading/learning Java and Scala right now for my internship, and theyre much less painful experiences because even though I dont have a specific background in those languages, I have a background in general programming and thinking algorithmically/like a CS student. My journey through Course 6-3 is only half over, anyways. I have yet to take 6.031 (I will in the fall), which is like, the  software engineering class, among lots of other fun things. :) Why did you choose Course 6-3? Initially, when I came to MIT, I had no idea what I was going to do, except that I was into math and probably wanted to go into computer science. My dad was into electrical engineering and did programming as a hobby, going as far as getting a software engineering job for a short time in Korea before quitting and moving to the States. So I had a little bit of exposure to programming, but not much. I picked up a couple programming books when I was younger (Visual Basic 6, C++) but didnt get very far because it was all too confusing at the time. I did read a fair amount about Java my senior year of high school, so going into MIT I had a little bit of programming knowledge that served as a really nice cushion while I was taking 6.0001. I took 6.01 and 6.042 after 6.0001 because I wanted to see what the EECS department as a whole was like (motivation to take 6.01) and wanted to see what math in a CS lens was like (motivation to take 6.042). I thoroughly enjoyed both classes, and it was at that time I knew that I wanted to go into some version of Course 6. If I didnt like 6.042 or 6.01, I probably would have tried a different major, probably Course 18 or Course 2-A. To be honest, I could easily be Course 6-1 or 6-2 instead and still be happy: I really enjoyed learning about signals and systems, circuits, and low-level stuff in 6.004. But I think I liked programming just a *little* bit more to stick to 6-3 instead of the others. I appreciate the thought and design that goes into programming languages just as much as the structure of human language (linguistics is cool), even though Im still a noob when it comes to programming language design stuff. Ultimately, I chose to go for an applied 6-3 route instead of a theoretical 6-3 route or 18 because although I love mathematics very much, I get satisfaction and pleasure from working on projects that have relatively immediate positive impacts on other people, and I feel like I get more of that from doing 6-3 over 18. So thats the end of it, for now. Course 6-3 is a really big community with a lot of really great people, some amazing professors, and a lot of opportunities. Obviously, some classes wont hit the mark for you, whether it be the subject matter or bad course management or instructors. This varies with time: 6.036 used to be run poorly (according to general sentiment), but now its pretty alright! Overall, its a great time, and even though it has its stereotypical traits mentioned in the very beginning of this post, its genuinely a rewarding intellectual experience as well. The class list above will be edited over time as more responses come through from friends and others: if youre an alum or someone who has more things to say about Course 6-3, feel free to comment or let me know and I might add your thoughts! :)