Defining complexity for visual-spatial memory tasks and human operator’s throughput

In this paper we study effectiveness and efficiency of HCI tasks that involve visual-spatial memory. Based on the Fitts’ law model that is widely used to model human motor reactions and inspired by Gestalt principles of human perception, we proposed formulation for index of difficulty for these tasks. The index includes the number of memorized information chunks, the size of vocabulary for the displayed objects (representing the diversity of elements), and the size of the working area, where the visual search and memorization are performed. We performed experiment with 88 subjects and the analysis of the collected data suggested that the information chunks were not elemental objects (squares), but figures composed based on range 1 von Neumann neighborhood known from cell automata. Based on the proposed index of visual-spatial memorization difficulty, we calculated throughput, which in our experiment was 3.75 bit/s (4.07 bit/s for male subjects and 3.61 bit/s for female ones).