The Loss of Confidence Project encourages professors to embrace the times when they’re wrong.
Three years out of teaching from university and from time to time I find I still have to deal with students…which is a welcome respite, actually, as it takes me out of the usual challenges at work, even if only for some brief moments.
The latest interaction came out of the blue. An industrial engineering student texted me to ask if we had any problems that could be solved by “various IE tools.” She had been referred to a former colleague and now professor at the local university. Rather than continue the conversation by SMS, I decided to call her up instead.
The scientific publishing ecosystem is a big rip-off, charging authors to publish and readers to read.
One day someone asked me to endorse the textbook for a course that was to be taught to all university freshmen. Okay, I said, but I’d like to go through the book first, just so I knew what it was I was endorsing.
As I flipped through the pages, I was somewhat put off by the incongruous presentation of the material. Not that there was anything egregiously wrong with it, but the chapters felt like they didn’t flow smoothly. I initially shrugged it off. After all, they would have been using some variation of the same textbook, and this did come from a reputable publisher. If that was what the department wanted to use….
…what I suspected all along and what was fuelling my disappointment with academia. Alright, maybe too broad a generalization but I’ve found many PhDs to be a little lopsided in their outlook, often unable to relate to people outside their field. This program aims to change that: Training PhD students to be thinkers, not just specialists.
…or so articles like these make me think: We Should Not Accept Scientific Results That Have Not Been Repeated. The article points to what is now known as the irreproducibility crisis, meaning, many of the findings published in high impact journals cannot be repeated. While not necessarily pointing to outright fraud, there are other possible reasons such as technical, statistical, and personal biases. The net of this is: scientists are driven by the need for recognition, and this can oftentimes skew results.