Word Superiority Lab

Data:

Lab Questions

●        How does the pattern of your individual data relate to the pattern of results predicted?

Researchers predict that responses will be faster and more accurate for actual words than they will be for non-words (Goldstein, 2019). My results were consistent with this prediction. I was quicker to identify words and I was faster to respond to them than I was with non-words.

●        What does this lab tell us about reading as a bottom-up or top-down process? What do you think would happen when learning a new language?

Reading is a complex combination of top-down and bottom-up processing. When we see the words, we must send them to our brain for interpretation (bottom-up). Once we know what the words are, we must use our previous knowledge to understand their meaning within the context they’re appearing (top-down). Learning a new language would make reading more difficult because there wouldn’t be a vast amount of previous knowledge to interpret words and sentences like there is in our native languages. The top-down processing portion of reading in a foreign language would also involve an extra step of filtering the word through your native language, which will likely take more time than simply reading in your native language.

Lexical Decisions Lab

Data:

Lab Questions

●        How does the pattern of your individual data relate to the pattern of results predicted?

Researchers predict that response times will be quicker when the second word is semantically associated with the first word than when the two words are unassociated (Goldstein, 2019). My results did not follow this pattern as I was slightly quicker to recognize unassociated words than I was to recognize associated ones. My kids did run in interrupting me a few times, though, so I’m wondering if this distraction had an impact on my results.

●        What does this lab suggest in the role of top-down processing when reading? What does it reveal about a “web of concepts”?

Top-down processing when reading allows us to essentially predict what the next words will be and create an image of what’s going on in our mind. As words can be semantically related with one another (like ‘window’ and ‘pane’) it becomes easier to use this previous knowledge to predict what might happen next within a story. Our brains aren’t like dictionaries, where everything is ordered alphabetically, but rather, our brains function like a web of concepts with certain words branching away and connecting to other words and meanings (Goldstein, 2019). In a complex and intricate web of concepts, we can draw meaning and predictions about the world around us at a rapid pace.

Module Question

●        These labs are all about recognizing elements of your language quickly and accurately. We tend to think of reading as a passive skill because it’s automatized. What do you think these labs tell us about what needs to happen for artificial intelligence (think Alexa and Siri) to recognize and process language as quickly and efficiently as we do? What do you think we are still better at doing compared to AI when it comes to language?

Reading is a very active skill that happens so quickly, we don’t always recognize the processes behind it. We have a huge collection of words and meanings that we’ve gathered in our heads our entire lives. Unlike artificial intelligence that also has a vast knowledge bank, we as humans are able to create meaning from these concepts and predict what may happen next. Artificial intelligence is programmed to have certain responses to certain commands and, while there could be multiple to choose from, the responses are limited to what’s been uploaded into the software. Humans alternatively can use what’s already in our ‘hardware’ to construct and develop meanings that may have not previously existed, but we know are likely to happen. In order to recognize and process language as quickly and efficiently as we do, artificial intelligence would have to allow some semblance of imagination to create meanings out of objective data. When it comes to language, humans are currently better than AI at being able to assign valuable meaning to the story we’re reading or telling. This allows us to predict what may occur next and assign emotion to the story as well, both things AI is not yet capable of accomplishing.

References

Goldstein, E. B. (2019). Cognitive Psychology (5th ed.) Cengage. https://www.cengage.com/