AP Language and Composition
February 28, 2014
This paper looks at the idea of interpreting dreams and understanding if they can show us something special. The writing also dives deep into the different kinds and categories of dreams we have every other night. The research in this paper comes from a number of psychological references that have conducted research about the subconscious activity in the brain. This writing takes into consideration that perhaps, not all dreams can be interpreted. However, there is substantial evidence to support the fact that some dreams do have meaning. As opposed to the conscious mind, this shows the possibility that dreams may actually be a form of self-discovery.
Interpreting Dreams and Dream Types
Almost every culture throughout time has tried to develop ways of interpreting dreams. But today many people believe that search has been unsuccessful. Scientists have even said that dreams are just random signals sent from primitive regions of the brain, meaning nothing, and that trying to interpret dreams is some sort of superstition. This conclusion is premature. For many years, researchers have been using quantitative methods of analysis to study the content of dreams. The findings from some studies provide compelling evidence that dreaming is not meaningless “noise” but rather a sophisticated mode of psychological functioning.
Recent advances in digital technology are expanding this approach, potentially boosting the magnitude of our ability to understand the statistically recurring patterns in people’s dreams. You could say that we are learning how to “data-mine” dreaming. The earliest work in the quantitative study of dream content goes back almost a century ago, to a Wellesley psychologist named Mary Whiton Calkins. Her 1893 article “Statistics of Dreams” described one of the first scientific experiments devoted to dream content. Calkins and a colleague kept journals of their dreams, recording each one upon awakening. She collected a total of 375 dream reports, each of which she analyzed and “coded” for several categories of content and then tabulated to determine which elements appeared most often. She found that the content of these dreams usually included realistic settings, lots of familiar characters, “the dream world is well peopled” (Bumb 2001). Calkins used fairly simple tools and a small data set to identify patterns in dream content, but later studies have largely confirmed these insights and extended them to new groups of people. For example, we now know that “artists are more likely than non-artists to have nightmares and that younger people are more likely than older people to have “lucid” dreams” (Goleman 1984). The emergence of modern digital-search technology has raised the intriguing possibility of pushing Calkins’ rather slow and labor-intensive approach to new levels of speed and sophistication. To take the first step in exploring that possibility William Domhoff at the University of California has conducted several experiments to confirm Calkins predictions. Here’s how it works. A colleague sends Professor Domhoff an electronic file of dream reports from a participant whose identity is hidden from him. Without reading the narratives of the dreams, he uploaded the file into a computer program designed for this purpose. The program enables the use of a word-search template to analyze the reports. The template includes categories for perceptions, emotions, characters and many other common features of dream content. For each category he compared the word-usage frequencies of an individual’s dreams with those from previous studies of dream content, looking for unusually high or low frequencies that might signal a meaningful connection. Then he made inferences about the person’s concerns, activities and relationships in waking life and send