- 8 reviews
- 8 completed
The course title has ambitious scope. As it is, it's a series of overviews of many works of philosophy, literature, and art, with a strong focus on the development of photography. The first half of the course was highly enjoyable and exposed me to the ideas and works of many thinkers that I had never encountered before. This course wasn't hard at all in terms of getting a high grade: you can get points just for claiming to have viewed course content. The material was challenging on its own merits (though this had nothing to do with the course design, which seems set up purely to provide students with a wide survey.) Probably the biggest merit of the course is its framework of analyzing ideas as two-level theories, including both manifest and latent segments, and in its meta-approach to philosophers (looking at the structure of their philosophy and not just the content.) There were, however, many things that went wrong with the course: 1.) There was far less content towards the latter half of the course. Readings, if present, were mostly truncated to only a couple of paragraphs. There was far less philosophy and literature in the latter half of the course as well. About 2/3 of the course content was in the first six weeks. 2.) Towards the latter half of the course, each week became almost exclusively focused on a bunch of history segments and an art/photography/cinema segment or two. The history segments were exclusively focused on what was going on in the United States, discussing the acts of US presidents and the like, and after the WWII segment pretty much ignored developments in the rest of the world. In short, it didn't feel like "ideas of the twentieth century" anymore. 3.) There was questionable balance in the views and summaries expressed, particularly regarding political issues such as the legacy of certain presidents. To be more precise, there was a bit of a right-wing (in the American political sense) bias in the course. It was a pretty interesting viewpoint, however, considering that professors on average have more of a left-wing bias. 4.) Three essays were required in the course, and unlike every other course that uses peer review, this one decided to experiment with an automatic grader that would grade based on a rubric and a pattern developed from the professor's personally grading about 150 essays per topic. This is more of EdX's fault, but the automatic grader frequently crashed or failed to grade essays until certain conditions were fulfilled. When it did work, it predictably applied very narrow criteria and seemed to operate via searching for keywords. Whether or not this reflects flaws in the grader or reflects the professor's grading style is still an open question. 5.) Discussion forums were a mess. EdX has poor discussion forums in general, but for some reason, philosophical and historical topics were mostly assessed with multiple choice quizzes while the art and photography sections were mostly assessed with discussion questions, resulting in forums filled with posts that were just replying to the given discussion prompt. Trying to post about another topic was generally futile, as no one would see your thread unless they were specifically searching for the topic you were talking about. This sort of thing plagues other EdX courses such as Harvard's ChinaX as well, though it's been solved in other EdX courses (e.g. 7.00x, 8.01x, 6.00.1x) by providing an open discussion forum in every segment of the course material. The latter two problems are more platform-specific, so I can't really fault this course for those, but the first three problems indicate to me that the enthusiasm and effort put into the course pretty much bottomed out after half of it was done.
This was an excellent course, half of a first course in computer science covering basic algorithmic thinking, functions, loops, recursion, debugging, searching and sorting, orders of growth, object-oriented programming and trees. This is less of a programming course than it is a computer science course, because a lot of programming details (syntax, built-in functions, etc) is only briefly mentioned and you're expected to do some research yourself using the Python documentation, etc. This was a nicely difficult course that included interesting problem sets where you build something step by step. CONS: \- There were a few errors in the lectures and some very ambiguous wording in the problem sets, but most of the time the course staff took an attitude of "we're always right and you're probably just doing it wrong" towards the students. I can't blame them, though, as there were also a lot of unjustified complaints by students. \- I have to mention it again: some of the problem sets, exams, exercises, etc. had very poor (sometimes contradictory) wording, such as a problem concerning family trees on the final exam. As a result, a lot of people made mistakes not because they didn't understand course concept, but because they were wrestling with how the specifications were worded, trying to guess what the grader was looking for. \- During the first run of this course, edX graders frequently crashed during exams. The course staff would move deadlines to get around this, but it was inconvenient for many people with a tight schedule who could only take the exam during a small window of time. With that said, I hope that the next offering of this course cleans up errors instead of just recycling everything. This was an excellent and rewarding course to take, but it definitely leans more towards the theoretical, math-heavy side of computer science.
This is a perfect course for people with absolutely no programming experience. It teaches one language, Python, in a very slow-paced manner (one week for for-loops, another for while-loops, and another for for-loops OVER INDICES), but it manages to cover enough in seven weeks for its students to become comfortable with the very basics of Python and be able to explore new things on their own. In particular, taking this course first has helped me keep up with the much faster-paced Introduction to Interactive Programming in Python from Rice University on Coursera, and Introduction to Computer Science and Programming with Python from MIT on EdX. Taking this course first has allowed me several weeks to get comfortable with things like iteration and string manipulation. The teaching is fairly decent, though the professor's voices can lull you to sleep at times. The majority of videos are taken up by the IDLE interpreter, with the professor/s typing out programs as they speak. The professors make a lot of typos which they then correct in the same video, which was good because everyone makes typos and it helped emphasize how small things can lead to total program failure. The instructors also made extensive use of the Python visualizer tool to emphasize the logic of how programs are executed, which helped me understand recursion later on in a separate course. The assessments were surprisingly challenging. The quizzes were pretty tricky and featured many debugging problems (what's wrong with this code/which of these programs will work?). Many people sweated for days on the three problem sets/assignments, but the assignment writeups were written very well, allowing sufficient guidance but not giving away the answers. Here's an example of an assignment (a word search game): http://spark- public.s3.amazonaws.com/programming1/a3/a3.html This course is recommended for anyone who wants to learn the very basics of programming. But people with even just a little bit of prior experience may find the pace way too slow.
Social Psychology was the most popular course on Coursera in terms of how many people signed up for it. As you'll notice from the reviews, however, appraisals of the course are rather polarizing. Either you love the course or you extremely hate it. I'm giving the course five stars for what I thought was excellent treatment in general from the course staff, even though there were many, many things that went wrong. PROS: \- This is not a fluffy course. The workload is huge - there are many lecture videos, a writing assignment and around 40 pages of reading every week. Videos alternate between documentaries borrowed by the professor for the course and lecture videos by the professor, and the treatment is generally rigorous. Social psychology contains many counterintuitive insights about the human condition, and the professor takes great care to back his assertions up with experimental research and meta- analyses. Much of the pedagogy in this course rests on overturning common sense. The professor assidously provides sources to journal articles, etc. for every single thing he says. This is what I cared most about in the course: it was a relatively difficult course and the content was worth it. \- The professor's style is engaging, with some of the videos having gags or even mini-experiments to keep the viewer engaged. \- There are "bonuses" in the course, like one winning final assignment essay being chosen to meet the Dalai Lama, and nine others being given money to donate to the charity of their choice; small group discussions for extra credit; and documentaries obtained through the professor's connections such as footage of the Stanford Prison Experiment and the Milgram shock experiments. One creative touch was how at the beginning of the course students were asked to complete an ungraded "Snapshot Quiz" with various questions relating to social psychology. Your personal answers to that quiz were then continually brought up in the middle of lectures when that relevant topic was being discussed. CONS: \- Everything in the course is provided for free, but the professor frequently encourages people to become a member of his Social Psychology Network for $10. One of the assignments featured the SPN as well, though there was an alternate assignment available. I completed the course fully without paying a cent, but it was somewhat off-putting. \- Many people on the forums expressed reservations about whether the course or some aspects of the course served the professor in some way. For example, the assignments frequently involved some aspect of the professor's work (for example, being asked to assess the persuasive effect of an anti-smoking website developed by the professor, or being asked to complete and then write about an online interview questionnaire about animal rights developed by the professor). Some wondered whether the entire course was an experiment in social psychology. \- The videos in the course were not downloadable, unlike in most other Coursera courses. This meant that many people could not download the videos for later, they had to have an Internet connection all the time. The professor's explanation was that he made extensive use of copyrighted material and in exchange had to agree not to allow downloading. I'm sure a lot of people dropped the course because of this inconvenience. \- While the professor did not proselytize, there's no denying he wore his more political beliefs on his sleeves - such as the aforementioned assignment on animal rights. This might have sometimes spilled over into the lectures, such as how the professor spent quite a while discussing the literature on how violence on TV affects aggressiveness, then right before the end of the video extrapolates to video games and encourages people to avoid violent media. Many people complained on the forum that the research literature still has mixed results on video games and aggressiveness. I do hope that these shortcomings will be worked on, although not many professors make changes to their MOOCs once they've been released. Even as it is, however, the pros weigh enough for me to honestly recommend this course.
This was an excellent introductory course with good content and presentation. The "mapping labs" that invited students to explore the proprietary software ArcGIS as well as learn how to create and analyze different sorts of basic maps were the meat of the course. There was very little video content, and with the exception of excerpts from a documentary, everything contained in the lecture videos could also be read in a text format (that wasn't just the script of the video, mind you). The content itself was basic but very insightful, going into design and methodology issues such as normalizing population, extrapolation, and selecting appropriate colors that seem obvious but are actually not taken into consideration by many mapmakers such as government agencies. The discussion forums were quite decent, although because there was a graded discussion requirement that made students post at least 20 times in order to get full credit, a lot of shallow and superfluous threads and comments were created. The professor was frequently present in the forums, and he even held an "ask me anything" session for three hours. This course only gets four stars from me, however, because I found it difficult to relate to the mapping labs and to complete the final mapping assignment. Many of the labs relied on datasets from the United States, whereas I live outside the USA and found it difficult to relate to activities like having to map natural disasters or identify unique geological features using datasets that only had information for the USA. This was one of the factors that led me to not complete the final assignment where you created your own map, subject to peer review - if I'm going to use ArcGIS, where am I going to get a dataset? I'm sure I could have worked these issues out with much more time, but perhaps one of my suggestions for a future run of the course is to include a module on sources of data and how to work with datasets.
This is a very easy course, and that's precisely its strength - it's a great course for introducing people like me who don't have any idea at all how the Internet works to topics such as the history of the Internet, layered network architecture, and encryption. Charles Severance is an engaging lecturer with a penchant for memorable metaphors, and as an added bonus, his other jobs as a writer for IEEE Computer Magazine and as the host of an old talk show about the Internet provide a wealth of material to the site, mostly interviews with Internet luminaries such as Robert Cailliau (co-inventor with Tim Berners-Lee of the WWW), Mitchell Baker (Mozilla Foundation), Bob Metcalfe (Ethernet; Wi- Fi is a variant of Ethernet), etc. To add to that, it's clear that Dr. Chuck (Severance) has put a lot of thought into running a MOOC, and has made several tweaks to the course since its first run (unlike a certain other University of Michigan colleague of his), such as making peer reviews optional and including a special lecture discussing how to do peer reviews and what plagiarism was. It's clear that effort was put into the multiple-choice quizzes as well, as some of the questions change with each attempt. And finally, I'm not entirely sure how, but this class had one of the best discussion forum environments on Coursera. There were no trolls or arbitrary attacks, there was no spam, and there was a lot of good humor, insightful stories and a ton of information shared. This is an excellent course for newbies, but even people who know a little bit about the Internet will find some value in the content.
This course is an excellent overview of various models used in the field of the social sciences. There's a lot to like about the scope and breadth of the topics. However, the most recent run of the course was quite poor. Staff was totally absent from the course - it was a fully automated process, which I presume means that that's how all future runs of the course will be. Unfortunately, there were still numerous errors in the course material, ranging from simple arithmetic errors to deeper errors in the way something was explained, etc. At one point during the last week he repeatedly refers to an earlier model by a DIFFERENT name than the name he used weeks ago, causing no end of confusion. Unless everybody involved in setting up the course was just taking a break for the summer, I think it's reasonable to assume that those errors are going to stay there in the next run and never be fixed - after all, the most recent run was already the 4th time for the course to be held, and the fact that basic errors haven't been fixed is telling. To add to that, many of the videos border on tedious. Professor Page is fond of going into every single mathematical step - even if it's just division - and doing it over, and over again, which is where the fast-forward button comes in handy. He is an endearing lecturer, however.
This course was probably one of the hardest things I've ever done in my life. I could devote maybe a couple of hours to most other MOOCs, watching videos and answering quizzes. This 13-week, 58-lecture (15 mins per lecture + some bonus material + homework PER lecture) course required me to twist my brain around almost every day, but Prof. Ghrist's snappy hand-drawn lectures (full of easter eggs to boot) made the experience far less painful. Scoring 50% or above is enough to pass the course, but that's not as easy as it sounds. And yes, even in the "real" version of this class, the passing grade is 50%. The approach to single-variable calculus is somewhat unorthodox. It assumes that you've had some previous exposure to calculus (knowing how to compute basic limits, derivatives and integrals, for example), and one of the very first things you learn is Taylor expansion. Applications not just in computing areas and volumes, but also in physics, statistics and probability are discussed. The professor also goes into discrete calculus towards the end. I felt a little bit of pride inside when in another class we were discussing error approximation, and the instructor said "we don't expect you to know error analysis, because you need to know Taylor expansion for that." If you want to know more about the scope of the material, you can visit the course wiki (open to all) at http://calculus.seas.upenn.edu/ under the "Single Variable" tab. Most importantly, Ghrist and his team didn't just dump a bunch of slick videos and quizzes online and call it a day. In the last run, Prof. Ghrist himself and his teaching assistant, Dr. Garcia-Raboso, were very active on the forums, providing inputs to people's concerns and clarifications. Glitches and typographical errors were quickly addressed by the course staff. Thus I really was in a class, and not just in an automated system. It's hard to find anything to criticize about the course. A few did not like the style of the lecture videos and complained about the professor's voice/delivery or the cartoonish feel, and others were uncomfortable with Taylor series being introduced so early but its full implication being reserved for the very last part of the course. Personally, I found this course one of the most fulfilling things I've done - it really takes a lot of grit to survive. My estimate is that only around 600-700 people took the final exam. It's an excellent launchpad for other courses that require calculus as a prerequisite, and there is no sacrifice in rigor and difficulty caused by the MOOC format whatsoever.